Search Results (67)

Oocytes and cumulus cells undergo meiotic resumption and proliferation via gonadotropins and growth factors during maturation, and various small G proteins are activated when COCs undergo physiological changes. This study investigated the influence of gonadotropins and growth factors on Ras and its GTPases during porcine COC maturation. Unmatured COCs were treated with FSH, LH, or EGF for 44 h. The mRNA expression levels of the Ras subfamily (H-Ras, K-Ras, N-Ras, and R-Ras), its GTPases (RASA1 and SOS1), and proliferation factors (ERK, CCNB1, and Cdc2) were analyzed using RT-PCR. In contrast to other Ras subfamilies, R-Ras expression is upregulated during COC maturation. We evaluated the effects of FSH, LH, and EGF at various concentrations that most effectively regulated the expression of R-Ras and GTPases. The results demonstrated that 0.5 µg/mL FSH, 10 IU/mL human chorionic gonadotropin (hCG), and 10 ng/mL EGF effectively enhanced R-Ras expression and cell proliferation. FSH supplementation during porcine COC maturation significantly upregulated R-Ras and ERK expression, independent of LH and EGF, and downregulated Cdc2 expression. These results indicated that FSH regulates R-Ras expression, thereby promoting cell proliferation during COC maturation. These results provide fundamental knowledge for understanding the role of Ras and its family members in the development of follicular environments in pigs. Full article

The present study constitutes the latest in a series of investigations conducted between 2021 and 2023 as part of the ongoing, multidisciplinary research project at the UNESCO archaeological site of Umm ar-Rasas in Amman Governorate, Jordan, which began in 2013. Building on the foundations of previous studies, this latest research offers a comprehensive analysis of the region, with a special focus on pinpointing the boundaries of the Byzantine–Umayyad settlement. The delineation of these boundaries has hitherto been the subject of theoretical discourse only, thus rendering this study a significant addition to the field. An innovative multi-dimensional, multi-methodological, and multi-scalar approach has been adopted, incorporating the capabilities of remote sensing technologies, archaeological surveys, laser scans, and geophysical prospecting to facilitate a shared interpretation of the results. This approach has culminated in the establishment of a probable configuration of the northern limits, which is truly remarkable. Full article

The development and use of conversational agents in education has become widespread in recent years because of their ability to facilitate student interaction with the learning material, improve engagement and provide academic support, while at the same time reducing the teachers’ workload. This is especially important in the case of distance and asynchronous education, where the availability of academic support must be ensured at any time. This paper reports on the implementation and evaluation of a conversational agent called AIMT Agent, developed for the purposes of supporting postgraduate students during their studies. The conversational agent is based on an open-source framework, namely Rasa, which provides the tools for building natural language understanding into the agent. The agent is fully integrated with the Moodle Learning Management System (LMS). The agent was assessed through a questionnaire according to the Technology Acceptance Model (TAM) in terms of perceived usefulness and perceived ease of use by 24 postgraduate students. The results show that users of the AIMT agent have assessed the conversational agent favorably in both of these aspects. This confirms the validity of the approach and is a motivation for refinements and further development. Full article

Objective: Rat sarcoma (Ras) proteins, Kirsten, Harvey, and Neuroblastoma rat sarcoma viral oncogene homolog (KRAS, HRAS, and NRAS, respectively), are a family of GTPases, which are key regulators of cellular growth, differentiation, and apoptosis through signal transduction pathways modulated by growth factors that have been recognized to be dysregulated in PCOS. This study explores Ras signaling proteins and growth factor-related proteins in polycystic ovary syndrome (PCOS). Methods: In a well-validated PCOS database of 147 PCOS and 97 control women, plasma was batch analyzed using Somascan proteomic analysis for circulating KRas, Ras GTPase-activating protein-1 (RASA1), and 45 growth factor-related proteins. The cohort was subsequently stratified for BMI (body mass index), testosterone, and insulin resistance (HOMA-IR) for subset analysis. Results: Circulating KRas, and RASA1 did not differ between PCOS and control women (p > 0.05). EGF1, EGFR, and EGFRvIII were decreased in PCOS (p = 0.04, p = 0.04 and p < 0.001, respectively). FGF8, FGF9, and FGF17 were increased in PCOS (p = 0.02, p = 0.03 and p = 0.04, respectively), and FGFR1 was decreased in PCOS (p < 0.001). VEGF-D (p < 0.001), IGF1 (p < 0.001), IGF-1sR (p = 0.02), and PDGFRA (p < 0.001) were decreased in PCOS compared to controls. After stratifying for BMI ≤ 29.9 kg/m², EGFR FGF8, FGFR1 VEGF-D, IGF1, and IGF-1sR differed (p < 0.05) though EGF1, EGFRvIII, FGF8, FGFR1, and VEGF-D no longer differed; after subsequently stratifying for HOMA-IR, only FGFR1, VEGF-D, IGF1, and IGF-1sR differed between groups (p < 0.05). Conclusions: Several growth factors that activate Ras differ between women with and without PCOS, and when stratified for BMI and HOMA-IR, only FGFR1, VEGF-D, IGF1, and IGF-1sR differed; these appear to be inherent features of the pathophysiology of PCOS. Full article

Modern businesses increasingly rely on chatbots to enhance customer communication and automate routine tasks. The research aimed to determine the optimal configurations of a telecommunications chatbot on the Rasa Pro platform, including the selection of large language models (LLMs), prompt formats, and command structures. The impact of various LLMs, prompt formats, and command precision on response quality was analyzed. Smaller models, like Gemini-1.5-Flash-8B and Gemma2-9B-IT, can achieve results comparable to larger models, offering a cost-effective solution. Specifically, the Gemini-1.5-Flash-8B model achieved an accuracy improvement of 21.62 points when using the JSON prompt format. This emphasizes the importance of prompt engineering techniques, like using structured formats (YAML, JSON) and precise commands. The study utilized a dataset of 400 sample test phrases created based on real customer service conversations with a mobile phone operator’s customers. Results suggest optimizing chatbot performance does not always require the most powerful models. Proper prompt preparation and data format choice are crucial. The theoretical framework focuses on the interaction between model size, prompt format, and command precision. Findings provide insights for chatbot designers to optimize performance through LLM selection and prompt construction. These findings have practical implications for businesses seeking cost-effective and efficient chatbot solutions. Full article

Following the re-opening of the Rasa Trulnang Tsuklhakhang, the central temple in Lhasa, all of the new images of Buddhas, bodhisattvas, and famous lamas were placed behind glass except for those in the sancta sanctorum, the “Jokhang”. When a pilgrim approaches the central figure, the Jowo Śākyamuni, she climbs a ladder on his right side, lays a ceremonial scarf across his lap, and then lays her head there, like a child seeking solace from her mother. A wealthy pilgrim might return in the late afternoon, when the temple is closed to visitors, to sponsor a regilding ceremony, in which the sponsor can spend up to an hour nearly alone with the Jowo watching his whole body be repainted in gold. Based on participant observation, pilgrimage guides, and verses of praise offered to the Jowo, this paper considers how the cult of the Jowo uses moments of private intimacy to bridge the distance, both physically and historically, between a devotee and the Buddha. Full article

Suffering is a problem addressed by many world religions. This paper examines the understanding of suffering in three religions: Catholic Christianity, Shia Islam, and Shakta Hinduism. In each of these cases, ordinary suffering is transformed into mystical sorrow, becoming a path to closeness and divine union. This transformation makes use of religious symbolism of the family, emphasizing the role of the mother. Worldly suffering is no longer meaningless; instead, it becomes a spiritual path through which the individual person, and even the world at large, may be redeemed. Full article

This paper presents the results of research on the technical–economic optimization of FDM parameters (L_h—layer height and I_d—infill density percentage) for the manufacture of tensile and compression samples from recycled materials (r) of PETG (polyethylene terephthalate glycol) and ASA (acrylonitrile styrene acrylate) in the context of the transition to a circular economy. To carry out our technical–economic study, the fundamental principle of value analysis was used, which consists of maximizing the ratio between V_i and C_p, where V_i represents the mechanical characteristic (tensile strength or compressive strength) and C_p represents the production cost. The results of this study showed that, in the case of tensile samples manufactured by recycled PETG (rPETG), the parameter that significantly influences the results of the V_i/C_p ratios is L_h (the height of the layer), while for the samples manufactured additively from recycled ASA (rASA), the parameter that decisively influences the tensile strength is I_d (the infill density percentage). In the case of compression samples manufactured by FDM from recycled PETG (rPETG) and recycled ASA (rASA), the parameter that signified influences the results of the V_i/C_p ratios is I_d (the infill density percentage). Following the optimization of the FDM parameters, using multiple-response optimization, we identified the optimal parameters for the manufacture of parts by FDM from rPETG and rASA: L_h = 0.20 mm and I_d = 100%. The results of this study demonstrated that the use of recycled plastics from PETG and ASA lends itself to a production and consumption model based on a circular economy. Full article

This paper proposes using a web crawler to organize website content as a dialogue tree in some domains. We build an intelligent customer service agent based on this dialogue tree for general usage. The encoder-decoder architecture Seq2Seq is used to understand natural language and then modified as a bi-directional LSTM to increase the accuracy of the polysemy cases. The attention mechanism is added in the decoder to improve the problem of accuracy decreasing as the sentence grows in length. We conducted four experiments. The first is an ablation experiment demonstrating that the Seq2Seq + Bi-directional LSTM + Attention mechanism is superior to LSTM, Seq2Seq, Seq2Seq + Attention mechanism in natural language processing. Using an open-source Chinese corpus for testing, the accuracy was 82.1%, 63.4%, 69.2%, and 76.1%, respectively. The second experiment uses knowledge of the target domain to ask questions. Five thousand data from Taiwan Water Supply Company were used as the target training data, and a thousand questions that differed from the training data but related to water were used for testing. The accuracy of RasaNLU and this study were 86.4% and 87.1%, respectively. The third experiment uses knowledge from non-target domains to ask questions and compares answers from RasaNLU with the proposed neural network model. Five thousand questions were extracted as the training data, including chat databases from eight public sources such as Weibo, Tieba, Douban, and other well-known social networking sites in mainland China and PTT in Taiwan. Then, 1000 questions from the same corpus that differed from the training data for testing were extracted. The accuracy of this study was 83.2%, which is far better than RasaNLU. It is confirmed that the proposed model is more accurate in the general field. The last experiment compares this study with voice assistants like Xiao Ai, Google Assistant, Siri, and Samsung Bixby. Although this study cannot answer vague questions accurately, it is more accurate in the trained application fields. Full article

This in vitro study investigated how varying magnifications (5×, 10×, 20×, and 50×) using a confocal laser scanning microscope (CLSM) influence the measured surface roughness parameters, R_a/S_a and R_z/S_z, of various materials with two surface treatments. Cylindrical specimens (d ≈ 8 mm, h ≈ 3 mm, n = 10) from titanium, zirconia, glass-ceramic, denture base material, and composite underwent diamond treatment (80 μm; wet) and polishing (#4000; wet; Tegramin-25, Struers, G). The surface roughness parameters (R_a/S_a, R_z/S_z) were measured with a CLSM (VK-100, Keyence, J) at 5×, 10×, 20×, and 50× magnifications. Line roughness (R_a/R_z) was measured along a 1000 μm distance in three parallel lines, while area roughness (S_a/S_z) was evaluated over a 2500 μm × 1900 μm area. The statistical analysis included ANOVA, the Bonferroni post hoc test, and Pearson correlation (SPSS 29, IBM, USA; α = 0.05). R_a/S_a and R_z/S_z showed significant differences (p ≤ 0.001, ANOVA) across magnifications, with values decreasing as magnification increased, highest at 5× and lowest at 50×. Titanium, zirconia, and glass-ceramic showed significant measured roughness values from 5× to 50×. Denture base material and composite had lower measured roughness values, especially after polishing. Line and area roughness varied significantly, indicating that magnification affects measured values. Standardizing magnifications is essential to ensure comparability between studies. A 50× magnification captures more detailed profile information while masking larger defects. Full article

In this work, we describe the implementation of an infrastructure of conversational chatbots by using natural language processing and training within the Rasa framework. We use this infrastructure to create a chatbot assistant for the users of a bioinformatics suite. This suite provides a customized interface solution for omic pipelines and workflows, and it is named GPRO. The infrastructure has also been used to build another chatbot for a Laboratory Information Management System (LIMS). The two chatbots (namely, Genie and Abu) have been built on an open framework that uses natural language understanding (NLU) and machine learning techniques to understand user queries and respond to them. Users can seamlessly interact with the chatbot to receive support on navigating the GPRO pipelines and workflows. The chatbot provides a bridge between users and the wealth of bioinformatics knowledge available online. Full article

We developed an innovative system that combines Natural Language Understanding (NLU), a curated knowledge base, and the efficient management of a Large Language Model (LLM) to support motivational health coaching. Using Rasa as the core framework, we enhanced it by integrating the GPT-3.5-turbo model. Users opt into reflective dialogues during conversations. When they respond to open-ended questions, their input goes directly to the GPT-3.5-turbo model, allowing for more flexible responses. To provide curated trustworthy content, we integrated a knowledge provision component that searches a PDF-based knowledge base and generates user-friendly responses using Retrieval-Augmented Generation. We tested the system in a real-world scenario by deploying it on a Nao robot in seven older adults’ homes for 1–2 weeks, encouraging positive behavioral changes in some users. Our system serves as a valuable foundation for building an even more integrated, personalized system that can connect with other Application Programing Interfaces (APIs) and integrate with home sensors and edge devices. Full article

Rapeseed (Brassica napus L.) seedlings suffering from inappropriate growth substrate stress will present poor seedling quality. However, the regulatory mechanism for the production and scavenging of reactive oxygen species (ROS) caused by this type of stress remains unclear. In the current study, a split plot experiment design was implemented with two crop growth substrates—a rice growth substrate (RIS) and rapeseed growth substrate (RAS)—as the main plot and two genotypes—a hybrid and an open-pollinated variety (Zheyouza 1510 and Zheyou 51, respectively)—as the sub-plot. The seedling quality was assessed, and the ROS production/scavenging capacity was evaluated. Enzymatic and non-enzymatic systems, including ascorbic acid and glutathione metabolism, and RNA-seq data were analyzed under the two growth substrate treatments. The results revealed that rapeseed seedling quality decreased under RIS, with the plant height, maximum leaf length and width, and aboveground dry matter being reduced by 187.7%, 64.6%, 73.2%, and 63.8% on average, respectively, as compared to RAS. The main type of ROS accumulated in rapeseed plants was hydrogen peroxide, which was 47.8% and 14.1% higher under RIS than under RAS in the two genotypes, respectively. The scavenging of hydrogen peroxide in Zheyouza 1510 was the result of a combination of enzymatic systems, with significantly higher peroxidase (POD) and catalase (CAT) activity as well as glutathione metabolism, with significantly higher reduced glutathione (GSH) content, under RAS, while higher oxidized glutathione (GSSH) was observed under RIS. However, the scavenging of hydrogen peroxide in Zheyou 51 was the result of a combination of elevated oxidized ascorbic acid (DHA) under RIS and higher GSH content under RAS. The identified gene expression levels were in accordance with the observed enzyme expression levels. The results suggest that the cost of substituting RAS with RIS is a reduction in rapeseed seedling quality contributing to excessive ROS production and a reduction in ROS scavenging capacity. Full article

The rise of conversational agents (CAs) like chatbots in education has increased the demand for advisory services. However, student–college admission interactions remain manual and burdensome for staff. Leveraging CAs could streamline the admission process, providing efficient advisory support. Moreover, limited research has explored the role of Arabic chatbots in education. This study introduces Tayseer, an Arabic AI-powered web chatbot that enables instant access to college information and communication between students and colleges. This study aims to improve the abilities of chatbots by integrating features into one model, including responding with audiovisuals, various interaction modes (menu, text, or both), and collecting survey responses. Tayseer uses deep learning models within the RASA framework, incorporating a customized Arabic natural language processing pipeline for intent classification, entity extraction, and response retrieval. Tayseer was deployed at the Technical College for Girls in Najran (TCGN). Over 200 students used Tayseer during the first semester, demonstrating its efficiency in streamlining the advisory process. It identified over 50 question types from inputs with a 90% precision in intent and entity predictions. A comprehensive evaluation illuminated Tayseer’s proficiency as well as areas requiring improvement. This study developed an advanced CA to enhance student experiences and satisfaction while establishing best practices for education chatbot interfaces by outlining steps to build an AI-powered chatbot from scratch using techniques adaptable to any language. Full article

Prognoses for TNBC remain poor due to its aggressive nature and the lack of therapies that target its “drivers”. RASA1, a RAS-GAP or GTPase-activating protein whose activity inhibits RAS signaling, is downregulated in up to 77% of TNBC cases. As such, RAS proteins become hyperactive and similar in effect to mutant hyperactive RAS proteins with impaired GTPase activities. PCAIs are a novel class of agents designed to target and disrupt the activities of KRAS and other G-proteins that are hyperactive in various cancers. This study shows the anticancer mechanisms of the PCAIs in two breast cancer cell lines, MDA-MB-468 and MDA-MB-231. PCAIs (NSL-YHJ-2-27) treatment increased BRAF phosphorylation, whereas CRAF phosphorylation significantly decreased in both cell lines. Moreover, the PCAIs also stimulated the phosphorylation of MEK, ERK, and p90RSK by 116, 340, and 240% in MDA-MB-468 cells, respectively. However, in MDA-MB-231 cells, a significant increase of 105% was observed only in p90RSK phosphorylation. Opposing effects were observed for AKT phosphorylation, whereby an increase was detected in MDA-MB-468 cells and a decrease in MDA-MB-231 cells. The PCAIs also induced apoptosis, as observed in the increased pro-apoptotic protein BAK1, by 51%, after treatment. The proportion of live cells in PCAIs-treated spheroids decreased by 42 and 34% in MDA-MB-468 and MDA-MB-231 cells, respectively, which further explains the PCAIs-induced apoptosis. The movement of the cells through the Matrigel was also inhibited by 74% after PCAIs exposure, which could have been due to the depleted levels of F-actin and vinculin punctate, resulting in the shrinkage of the cells by 76%, thereby impeding cell movement. These results show promise for PCAIs as potential therapies for TNBC as they significantly inhibit the hallmark processes and pathways that promote cell proliferation, migration, and invasion, which result in poor prognoses for breast cancer patients. Full article