Background In recent years, skin health has garnered widespread attention, with hyperpigmentation disorders caused by excessive melanin deposition emerging as a particularly prominent concern. Tyrosinase, as the rate-limiting enzyme in the melanin synthesis process, has long been a major focus in the development of its inhibitors. However, only a limited number of tyrosinase inhibitors are currently available for clinical treatment of such disorders, and they are associated with certain toxicity concerns. Consequently, there is an urgent need to develop novel inhibitors that combine high efficacy with low toxicity. Recent studies have shown that deep learning technology exhibits strong capabilities in uncovering the intrinsic patterns of data and predicting the biological activities of compounds, providing a significant opportunity for the rapid screening of novel tyrosinase inhibitors. Methods Based on a dataset of tyrosinase-related compounds, this study constructed a deep learning model to predict compounds that inhibit tyrosinase activity. Using this model, we conducted activity predictions for 36,585 compound and selected the top 100 molecules with the highest prediction scores for screening and verification. Results Literature comparison revealed that 53 of these molecules had been reported to inhibit tyrosinase activity, providing initial support for the model’s reliability. After further screening based on specific criteria, 10 candidate molecules were ultimately selected for molecular docking studies. The docking results indicated that these molecules had good binding potential with the target protein, indirectly supporting the accuracy of the model’s prediction. The final experimental verification revealed that compounds 5 and 10 significantly inhibited tyrosinase activity and reduced melanin content.
Ayda Mussa Yousif Abdulrahman, Rafiduraida binti Abdul Rahman
This research aims to investigate the current operational status of the Ajman Police, focusing on identifying elements and issues that affect operational excellence. Using change management models, including Kotter's 8 Step Model and the ADKAR Model, the paper critically examines the hierarchical structure of the Ajman Police, its specialist groups, and their performance indicators. The problem statement highlights the negative impact of traditional and rigid organizational structures on innovation, responsiveness, and the limitations of implementing effective public safety measures, prevention, and community policing. The research design adopted is a qualitative methodology, and a sample of senior police officers was interviewed to record their views on the issues of operation and preparedness to change. In conducting the study, Semi-structured interviews were conducted with 10 participants. Results indicate that the Ajman Police has already ventured into technological advancements and civil policing. However, there are still gaps in continuous development, innovation, and the implementation of modern change management practices. The research proposes a culturally, operationally, and technologically oriented framework for change management, specifically tailored to the context of the Ajman Police. The study makes a significant research contribution to both the practice and theory fields by providing a guideline for a change management roadmap for the Ajman Police and other similar agencies, ensuring operational excellence in fast-changing environments.
Management information systems, Economic history and conditions
With the development of artificial intelligence (AI), AI-related technologies are being applied in many fields of medicine. Anesthesia is now widely used in surgery, emergency resuscitation, pain treatment and other fields. However, different from some other common biomedical signals, such as the electrocardiogram (ECG), electroencephalogram (EEG), and some other medical imaging or biomarkers could be easily processed and analyzed by AI-related models, how to collect the relevant data in the anesthesia process is still a challenge, that has led to little current work on combining AI and anesthesia. However, it can be foreseen that the combination of AI and anesthesia will become increasingly important. This paper presents a comprehensive review of anesthesia with AI based methods which have been now used in the preoperative phase, intraoperative phase, and postoperative phase. We first overview some crucial concepts of artificial intelligence, then discuss the related applications of artificial intelligence used in different phases of the anesthesia period, finally, we look forward to the future development of intelligent anesthesia. We hope through this review, we can provide comprehensive and objective guidance in AI-related anesthesia process to help anesthesiologists use more advanced AI techniques to diagnose and treat patients during the anesthesia period.
To study the influence of edge effects on the resin filling flow pattern in the RTM process of composite materials, the finite element software PAM-RTM was used to simulate and analyze the impregnation process of the blade preforms in RTM.By observing separately the filling time of the resin and the flow state of the leading edge in the impregnation process under the conditions with and without edge effect, the influence of different fiber volume fractions in the edge area and different injection pressure differences on the filling time and flow process of the blades was discussed, and the feasibility of the simulation method was verified through experiments.The results show that the presence of edge effect can prolong the length of the resin filling front, thereby reducing the impregnation time of the blade by 15.8%, but the difference in edge permeability does not significantly affect the impregnation time of the blade. When the edge effect exists in the fiber preform, different injection pressures have significant influences on the filling time.The filling time decreases with the increase of pressure, and the decreasing trend gradually slows down.The simulated value of the resin filling time differs by 7.8% from the measured value, indicating that the simulation method is feasible to a certain extent.
Materials of engineering and construction. Mechanics of materials, Environmental engineering
Patrick Michael, Robert J. Reid, Robert W. Fitzpatrick
The long-term roles of live plant roots in mitigating acid sulfate soil stresses remain poorly understood. Three studies, each lasting twelve months, were conducted using Melaleuca armillaris and Phragmites australis. In the first study, alkaline sandy loam soil was mixed into the sulfuric soil to increase the pH to 6.7, and Melaleuca seedlings were planted. In the second and third studies, M. armillaris and P. australis were planted in sulfuric and sulfidic soils and maintained at 75% water-holding capacity and flooded soil conditions. All the studies were set using 300 mm stormwater tubes with sealed bottom ends. The treatments were replicated four times, set up under a glasshouse in a completely randomized design, and harvested after 12 months. The pH and root biomass were measured from the surface, middle, and deep profiles. Results showed that the neutralization obtained by mixing alkaline sandy loam soil with sulfuric soil was stable but deteriorated due to plant root penetration. In the sulfuric soil material (pH <4), M. armillaris produced more roots at the surface than in the deep soil under circumneutral pH and aerobic soil conditions. In sulfidic soil material (pH >4), more roots were produced in the deeper soils. In the sulfuric and sulfidic soil materials, P. australis produced more roots at the surface than at the deep under pH >4 and aerobic conditions. Under anaerobic conditions with a pH >4, root distribution was even. Our findings suggest that common terrestrial and aquatic plants maintain a characteristic distribution of roots to mitigate the stresses of acid sulfate soils.
Abstract In order to further explore the effects of soil mercury pollution on soil microbial diversity and community structure, soil samples were randomly collected from 2 m, 20 m, 30 m, 500 m and 650 m periphery of Wanshan mining area, as 5 different treatments. Each treatment had 4 replicates. Soil microbial DNA was extracted from 20 soil samples, and then high-throughput sequencing technology was used to analyse the structure and distribution of bacterial and fungal communities. The results showed that the number of bacterial and fungal communities in T0–T30 treatments was significantly larger than that in T500–T650 treatments at order, family and genus level. Whatever, the number of uniquely distributed bacterial and fungal communities among 4 replicates soil samples was quite different at order, family and genus level. The results of the effect on the microbial community structure showed that there were both the same dominant bacterial and fungal communities, and the different dominant bacterial and fungal communities at any classification level, moreover, the number of same dominant bacterial and fungal communities was larger than that of different dominant bacterial and fungal communities. The results of relationship between soil environment factors and bacterial and fungal community structure showed that distance (Hg 2+ ), EC and pH had a high correlation with community structure, especially the distance factor, that is, the content of mercury in soil had the highest effects on community structure. The internal heterogeneity of soil caused significant differences in bacterial and fungal community structure, and the emergence of dominant bacterial and fungal communities was a manifestation of better adaptability to long-term mercury stress and other stresses in soil, which will provide a scientific reference for further exploring the mechanism of mercury enrichment between microorganisms and plants.
Ekaterina G. Nikulina, Ekaterina K. Starkova, Vera G. Ryabchikova
et al.
Problem statement . The modernization of higher education is a good ground for the use of electronic resources in ensuring accessibility, continuity and quality of teaching foreign languages. The use of interactive tools (simulators, flash cards, virtual whiteboards) meets the requirements to educational training programs for students of pedagogical directions and the challenges of modern society. A flash card is a card with a word, a concept, an image on one side and a translation on the other. The study aimed at substantiating the effectiveness of the use of flash cards for the formation of foreign language competence of future teachers. Methodology . Theoretical and methodological analysis and generalization were used to determine trends in the development of language education, the inclusion of informatization tools in foreign language activities and professional communication. The online platform Quizlet was chosen to work with ready-made flash cards and to create new thematic sets in digital format. The questions for the control work grouped into two blocks “Digital educational technologies” (50 points) and “Foreign language in professional communication” (50 points) were compiled. The study involved 54 students from Vyatka State University (the direction of 44.03.05 “Pedagogical education”, with two training profiles, bachelor's degree level). Pearson's chi-squared criterion was applied at the stage of statistical processing of the results. Results . The system of working with flash cards in the foreign language professional communication of future teachers is described: the study of the Quizlet functionality, working with ready-made sets of cards, automating and improving lexical units, developing their own thematic sets. In the course of independent work and network collaboration the students of the experimental group used Flashcards, Speller, Scatter, Quizlet Live modes. Statistically significant differences in the qualitative changes that occurred in the level of formation of foreign language competence were determined. Conclusion. The use of flash cards in the preparation of students of pedagogical specialties has a significant didactic potential for the development of their foreign language competence: the effect of immersion, competitiveness and obtaining positive emotions; resources for independent language learning in extracurricular time; overcoming the language barrier in the virtual gaming environment of information interaction. However, there are some drawbacks: monotony of forms for tests, lack of opportunity to practice pronunciation, partial support of operating modes in the mobile version.
Romeo Bandinelli, Gabriele Scozzafava, Bianca Bindi
et al.
The importance of traceability in food products in regard to consumer preferences, the difficulty of certifications in communicating credence attributes, and concerns about food safety, have led consumers to ask for more information about the credibility of information reported on the label with the product itself, due to the importance of traceability in food products. An objective of this study is to analyze the benefits of implementing blockchain technology in the supply chain for ancient wheat, as a technology capable of sharing reliable information about the products easily along the entire value chain. In particular, the aim is to evaluate how the consumer reacts when confronted with a package of ancient wheat pasta for which all the information on its origin and processing methods is available. In order to achieve these results, a survey based on the Technology Acceptance Model has been developed and conducted in the Italian country. Result indicates the importance of identifying an independent variable that represents the degree of security when faced with a threat that creates a circumstance, condition or event that can lead to economic hardship, for example, data destruction, disclosure, modification, fraud, waste, and abuse. The strength of blockchain lies precisely in its ability to guarantee the immutability of data throughout the supply chain, providing the end consumer with a high-quality product.
Systems engineering, Marketing. Distribution of products
China’s power industry is a major energy consumer, with the carbon dioxide (CO2) generated by coal consumption making the power industry one of the key emission sectors. Therefore, it is crucial to explore energy conservation and emissions reduction strategies suitable for China’s current situation. Taking a typical cogeneration enterprise in North China as an example, this paper aims to establish a generalized regression prediction model for carbon emissions of coal-fired power plants, which will provide a reference for China to seek strategies for carbon peaking and carbon neutralization in the future. Firstly, in terms of the selection of influencing factors, this paper uses objective index screening methods, simulation means, and the eXtreme Gradient Boosting algorithm (XG-Boost) to analyze the feature importance of various influencing factors. It is concluded that the relevant influencing factors of the boiler feed water system have a strong correlation and characteristic importance with the carbon emissions results of coal-fired power plants. Therefore, this paper proposes to introduce these factors into the regression prediction model as auxiliary variables to more scientifically reflect the carbon emissions results of coal-fired power plants. Secondly, in the aspect of regression prediction model establishment, inspired by the sparrow’s foraging behavior and anti-predation behavior, this paper selects the sparrow search algorithm (SSA) with strong optimization ability and fast convergence speed to optimize the super parameters of the long short-term memory network algorithm (LSTM). It is proposed to use the SSA-LSTM algorithm to establish the carbon emissions regression prediction model of coal-fired power plants. The advantage of the SSA-LSTM algorithm is that it can effectively simplify the super parameter selection process of the LSTM algorithm, effectively solve the global optimization problem, prevent the model from falling into overfitting and local optimization, and make the carbon emissions regression prediction model of coal-fired power plants achieve a better fitting effect. By comparing the performance indicators of the model before and after the improvement, it is found that the regression prediction effect of the SSA-LSTM coal-fired power plant carbon emissions regression prediction model, which introduces boiler feed water influencing factors, has been effectively improved. Therefore, the model proposed in this paper can be used to conduct a comprehensive impact factor analysis and regression prediction analysis on the carbon emissions intensity of China’s coal-fired power plants, formulate targeted carbon emissions reduction countermeasures, and provide a theoretical basis for energy conservation and emissions reduction of China’s coal-fired power plants.
Objective. We previously described that different concentration Nucleobindin-2 (NUCB2)/Nesfatin-1 gradients differently regulated visceral hypersensitivity in irritable bowel syndrome. Therefore, this study is aimed at evaluating the effect of NUCB2/Nesfatin-1 on model rats with chronic visceral hyperalgesia. Methods. Neonatal and mature Sprague-Dawley rats were randomly divided into the healthy control and chronic visceral hyperalgesia model groups. The model was built by combining maternal separation with the acetic acid enema. The models were identified by the distension volume threshold to reach abdominal withdraw reflex AWR score=3, histological staining, and myeloperoxidase (MPO) detection. The visceral sensitivity to chronic visceral hyperalgesia was then evaluated. Result. Rats in the model group responded more strongly to pulling stimulation than healthy controls; the distension volume threshold causing AWR3 response in model rats was lower than the control group before NUCB2/Nesfatin-1 intervention. After intervention, the distension volume threshold was significantly lower in the NUCB2/Nesfatin-1 central intervention group than in the NUCB2/Nesfatin-1 peripheral intervention group, and the peak value of external oblique muscle electrical activity was significantly higher. Additionally, compared with the male intervention group, in the female intervention group, the volume threshold was significantly lower and the peak value was higher. Conclusion. NUCB2/Nesfatin-1 could regulate visceral sensitivity in chronic visceral hyperalgesia model rats; its regulatory effect correlated with the type of NUCB2/Nesfatin-1 intervention approaches (central or peripheral) and sex (male or female).
A’am Rifaldi Khunaifi, Arif Supriyadi, Dedy Setyawan
Guru SMAN 1 Pandih Batu belum menggunakan Learning Management System (LMS) secara maksimal sehingga membutuhkan pelatihan dalam menggunakan aplikasi ini. Tujuan kegiatan ini adalah untuk meningkatkan pemahaman guru mengenai LSM khususnya menggunakan Sevima Edlink. Metode yang digunakan dalam pelatihan ini adalah demonstrasi, praktek, dan diskusi. Peserta pada kegiatan ini adalah 30 orang guru di SMAN 1 Pandih Batu. Target pelatihan ini yaitu guru mampu menggunakan Sevima Edlink, pembuatan topik materi, invite siswa, pengunggahan materi pelajaran, dan kuis daring. Hasil dari kegiatan ini menunjukan terjadi peningkatan kemampuan berdasarkan hasil pretest dengan nilai 62,3 meningkat pada hasil postest dengan nilai 80,5. Hasil skor N-Gain menunjukan terjadi peningkatan kemampuan guru sebesar 0,48 dengan kategori sedang. Peserta menilai bahwa pelatihan ini dapat memberikan manfaat berupa peningkatan pengetahuan dan keterampilan diri bagi peserta dengan metode ceramah maupun kegiatan demonstrasi dan peserta juga menilai bahwa pemateri baik ceramah maupun praktek sangat baik dalam penguasaan metode dan materi.
Food processing and manufacture, Academies and learned societies
Abstract Studying the wagon accumulation process and the laws of accumulation cost is of great significance for determining the suitable conditions of wagon accumulation and shortening the accumulation time. Here, the process of relaxed fixed time accumulation is first taken as a stochastic service system, and derives the theoretical formula for the accumulation cost. Then based on actual data of wagon flows, a simulation model is built to analyse the influence of parameters in the theoretical formula such as the coordination of the traffic diagram and the accumulation process, the sizes and intervals of the arriving wagon groups and the minimum number of wagons. Finally, through comparing with the accumulation cost of fixed train length accumulation mode and considering the benefit of changing the minimum number of wagons in train sets, the optimal minimum number of wagons in the relaxed fixed time accumulation mode under different wagon flow intensities is determined.
Liver is an important metabolic organ of mammals. During each transitional period of life, liver metabolism is programmed by a complex molecular regulatory system for multiple physiological functions, many pathways of which are regulated by hormones and cytokines, nuclear receptors, and transcription factors. To gain a comprehensive and unbiased molecular understanding of liver growth and development in Ningxiang pigs, we analyzed the mRNA, microRNA (miRNA), and proteomes of the livers of Ningxiang pigs during lactation, nursery, and fattening periods. A total of 22,411 genes (19,653 known mRNAs and 2758 novel mRNAs), 1122 miRNAs (384 known miRNAs and 738 novel miRNAs), and 1123 unique proteins with medium and high abundance were identified by high-throughput sequencing and mass spectrometry. We show that the differences in transcriptional, post-transcriptional, or protein levels were readily identified by comparing different time periods, providing evidence that functional changes that may occur during liver development are widespread. In addition, we found many overlapping differentially expressed genes (DEGs)/differentially expressed miRNAs (DEMs)/differentially expressed proteins (DEPs) related to glycolipid metabolism in any group comparison. These overlapping DEGs/DEMs/DGPs may play an important role in functional transformation during liver development. Short Time-series Expression Miner (STEM) analysis revealed multiple expression patterns of mRNA, miRNA, and protein in the liver. Furthermore, several diverse key Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including immune defense, glycolipid metabolism, protein transport and uptake, and cell proliferation and development, were identified by combined analysis of DEGs and DGPs. A number of predicted miRNA–mRNA–protein pairs were found and validated by qRT-PCR and parallel reaction monitoring (PRM) assays. The results provide new and important information about the genetic breeding of Ningxiang pigs, which represents a foundation for further understanding the molecular regulatory mechanisms of dynamic development of liver tissue, functional transformation, and lipid metabolism.
Building on the earlier net generation and millennials concepts, Prensky popularised the notion of a generation of “digital native” students through his 2001 two-part series “Digital natives, digital immigrants”. Although his ideas about how students perceive and utilise technology resonated with many educators, they lacked supporting evidence. Subsequent investigations, which informed the so-called “digital natives debate”, produced largely contrary evidence and dissenting views. As dissemination and acceptance of this evidence grew, interest in the idea of students as digital natives should have waned. However, a detailed analysis of general and academic search data and of articles published in leading educational technology journals (between 1998 and 2017) suggests that this interest remains strong. Although references to digital natives and the related terms net generation and millennials in educational technology journals has declined somewhat (having peaked in 2011), public and general academic search interest in these terms – and presumably the ideas that underpin them – continues to grow. These trends are discussed from an historical perspective, considering how our acceptance (or rejection) of the digital natives concept has developed, and the potential past, present and future impact of this on technology adoption and implementation practices within our universities.
This review describes the main features of dye-sensitized solar cells (DSCs) and highlights recent breakthroughs in this promising thin-film photovoltaic (PV) technology. After a brief presentation of the commercially available technologies, the general operation principles and the most relevant characteristics of DSCs are summarized. Recent major advances in high efficiency sensitizers, nanostructured semiconductors and robust electrolytes offer an opportunity for DSCs integration into the marketplace. With attractive features, like low-cost potential, simple processing, wide range of applicability – from low-power electronics to semi-transparent windowpanes for electricity generation – and good performance under typical operating conditions, these cells are one step from large-scale commercialization. We describe major strategies that are under way to make DSCs a key technology in the future PV paradigm.
Time series data is common in data sets has become one of the focuses of current research. The prediction of time series can be realized through the mining of time series data, so that we can obtain the development process and regularity of social economic phenomena reflected by time series, and extrapolate to predict its development trend. More and more attention has been paid to time series prediction in the era of big data. It is the basic application of time series prediction to accurately predict the trend. In this paper, we introduce various time series autoregressive (AR) model, moving average (MA) model, and ARIMA model that is combined by AR and MA. As the time series prediction in general scenarios, the ARIMA is applied to the risk prediction of the National SME Stock Trading (New Third Board) in combination with specific scenarios. The case studies show that the results of our analysis are basically consistent with the actual situation, which has greatly helped the prediction of financial risks.
Introduction. At present, the range of medicines for the treatment of mastopathy is represented, for the most part, by foreign manufacturers, which are currently not economically available to the general population of Ukraine. Structure of the range of medicines used in mastopathy therapy, by country of origin. Almost 44% of the assortment is domestic products. That is, these drugs provide both physical (availability at the place of sale of the drug) and economic affordability (the price of the drug suits the consumer). Given the need to implement the principles of import substitution, the development of original domestic preparations based on medicinal herbs for the treatment of mastopathy is relevant. The use of standardized drugs based on medicinal plant raw materials (MPRM) will allow more comprehensive coverage of all pathogenetic mastopathy pathways, reduce the dosage of synthetic chemotherapy drugs, and pay more attention to the quality of women's rehabilitation while maintaining their health and reproductive function. The importance of the above has led to the development of a new drug in the form of collection for use in gynaecology, which includes various types of MPRM, capable of effectively acting on all the etiological and pathogenic links of mastopathy. The pharmaceutical market of Ukraine has no analogues of a standardized herbal remedy for complex treatment of mastopathy, but the available ingredients have long been used in folk medicine. Material & methods. Based on the results of pharmaco-technological studies, a technological scheme of obtaining non-dosed and dosed species for use in the complex treatment of mastopathy was developed. Results & discussion. The main stages of the process of collecting and the critical parameters that are monitored at each stage are identified. The technology of collecting in different types of packing is described: in aluminium foil packs, plastic bags and “Doy-packs” and filter bags.Vegetable raw materials used for the preparation of the drug must be subject to input control for compliance with regulatory requirements. “Mastonorm” species technology includes the following stages of the production process: preparation of medicinal plant raw materials, production of “Mastonorm” species, weighting, packaging and marking of the “Mastonorm” species. For dispensing, there is a step of filling, packing and labelling “Mastormorm” species into filter bags. Conclusion. The technology of “Mastonorm” species was developed. The technological scheme of obtaining “Mastonorm” species in industrial conditions was developed. The technological industrial regulation of production of the “Mastonorm” species in different types of packing has been developed: plastic bag enclosed in cardboard packs; aluminium foil packs; “Doy-packs” and filter packages of 1.5 g № 20.
In this paper, the already strong McEliece cryptosystem is enhanced with atwo-dimensional finite Gaussian integer. By substituting the one-dimensional linear code with atwo-dimensional code employing afinite Gaussian integer, anew system simultaneously increases the key space and the errors to be correct by syndrome decoding. We compare the proposed system against the classic McEliece system in three aspects: the work factors performing the trial of the attacks, the computationalcomplexity cost, and the empirical running time of the system. Comparedto the classic McEliece cryptosystem,the enhanced cryptosystem achieves a higher security level against key recovering and decoding attacks. By carefully selecting parameters, asmall code element can improve the key strength without compromising the runtime efficiency.