Description Of Production Research Articles

Single inclusive hadron production at the LHC with an improved impact parameter dependent saturation model* *Supported by the National Natural Science Foundation of China (12165004, 11765005, 11947119); the Guizhou Provincial Science and Technology Projects (ZK[2023]027, [2019]5103); the Education Department of Guizhou Province, China (KY[2021]131); the National Key Research and Development Program of China (2018YFE0104700, CCNU18ZDPY04)

To obtain a reasonable description of the hadron production at the LHC energies, the impact parameter dependent saturation model is modified by inclusion of an anomalous dimension γ, which controls the slope of the scattering amplitude in the transition from the dilute region to the saturation region. We calculate the transverse momentum distribution and nuclear modification factor of the and charged hadrons with the improved model, and the results are consistent with measurements performed at the LHC. Moreover, we use the original impact parameter dependent model to study the aforementioned measurements performed at the LHC by adjusting its parameters. We find that the improved model is more consistent with the experimental data than the original one, as the anomalous dimension plays a significant role in the suppression of the evolution of the scattering amplitude.

Review on Satvapatana: A Process of Essence Extraction

Rasashastra is the Iatrochemistry of Ayurveda which deals with the various pharmaceutical processes of Shodhana (purification/potentiation), Marana (incineration/calcination), Jarana (polling), Murchhana (a procedure by which substances especially mercury is transformed for therapeutic application) and other detail description of metals, minerals, poisonous plants and animal products which are of therapeutic importance in Ayurveda. Satvapatana is one of the processes of Rasashastra for achieving the Satva (essence) of metals and minerals from their original source. The main objective of Satvapatana is to obtain the active component of ore and to minimise the dose of Dhatu without lowering its efficacy for therapeutic uses. The process of Satvapatana was first described by Acharya Nagarjuna in Rasendra Mangala. It has also been mentioned in other classical texts such as Anandakanda, Rasarnava, Rasa Hridaya Tantra, Rasendra Chudamani, Rasa Ratna Samucchayam, Rasa Tarangini. Satvapatana occurs in two stages which are Beejavarta and Shuddhavarta. Beejavarta indicates the melting of material and Shuddhavarta indicates the time for extraction of Satva. Satva of the different drugs is of different colours. The basic requirements for Satvapatana include Satvayukta Dravyas, Dravaka Varga, Musha, Koshti etc. Satva after extracting out is again subjected to Shodhana, Mridukarana and Marana processes to use for various therapeutic purposes. Mridukarana process is mentioned only in the case of Abhraka Satvapatana. Various uses of Satvas are mentioned in different classical texts such as Abhraka Satva for Charan and Jarana of mercury, Makshika Satva for Dehaveda and Lohaveda, Tuvari Satva for Bandhana of Rasa and Uparasa, Tuttha Satva and Bhunaga Satva for relieving pain, in wound healing etc. Satvapatana is an utmost process of Rasashastra not only for therapeutic uses but also for processing of mercury.

Trust and Purchase Intention Model of Muslim Z-Generation Consumers on E-Commerces (B2C) in Indonesia

<p><em>Indonesia is one of the countries with the highest number of online buyers. One of the potential target markets of e-commerce (B2C) is Z generation, a group of young people who spend most of their time accessing information from websites, including e-commerce. This study aimed to find out the effect of trust and purchasing intention model in the context of online shopping. This study used Structural Equating Modeling (SEM) approach. The sampling technique employed was convenience random sampling with a total of 300 respondents. This study found that perceived trust significantly impacts on purchase intention. Interestingly, perceived risk have negative effect on perceived trust while other variables, namely, product description, perceived site quality, enduring and sitational involvement have a positively effect on perceived trust</em></p>

PERLINDUNGAN KONSUMEN AKIBAT KERUGIAN YANG DITIMBULKAN PENERBITAN BROSUR PERUMAHAN YANG DILAKUKAN PENGEMBANG

The definition of promotion according to Article 1 number 6 of Law Number 8 of 1999 concerning Consumer Protection is the activity of introducing or disseminating information on goods and/or services to attract consumers' buying interest in goods and/or services that will be and are being traded. As we all know, brochures are one of the promotional media that are often used by businesses as a means to market a product or service. Usually brochures contain pictures and product descriptions that businesses want to market and usually product marketing through brochures is carried out in crowded places such as malls, streets or places that are deliberately provided such as exhibitions. Advertising through the brochure is also to attract consumer buying interest in the products being traded, in this case housing. However, behind the promotional activities using this brochure, there are many negative things done by the developer (developer), it is not uncommon for the public's trust to be misused by the developer. In making housing offers, it is not uncommon for the information provided by the developer to be too much so that it makes consumers very interested or maybe even confusing for the consumers themselves, the purpose of this research is to provide legal protection to consumers who are harmed by brochures promoted by developers that are not in accordance with the truth stated. If there is, then with the existing problems, this research uses normative legal research, which is a process to find a rule of law, legal principles, or legal doctrines to answer the legal issues at hand.

Intelligent online selling point extraction and generation for e‐commerce recommendation

AbstractDuring the past decade, great significant advancements have been witnessed in the domain of automatic product description generation. As the services provided by e‐commerce platforms become diverse, it is necessary to dynamically adapt the patterns of descriptions generated. The selling point of products is an important type of product description for which the length should be as short as possible while still conveying key information. In addition, this kind of product description should be eye‐catching to the readers. Currently, product selling points are normally written by human experts. Thus, the creation and maintenance of these contents incur high costs. These costs can be significantly reduced if product selling points can be automatically generated by machines. In this paper, we report our experience developing and deploying the intelligent online selling point extraction (IOSPE) system to serve the recommendation system in the JD.com e‐commerce platform. In addition, an interactive tool is released for merchants in JD.COM, which additionally allow them to select and customize the selling points with flexibility. Since July 2020, IOSPE has become a core service for 62 key categories of products (covering more than four million products). So far, it has generated more than 0.1 billion selling points, thereby significantly scaling up the selling point creation operation and saving human labor. These IOSPE‐generated selling points have increased the click‐through rate (CTR) by 1.89% and the average duration the customers spent on the products by more than 2.03% compared to the previous practice, which are significant improvements for such a large‐scale e‐commerce platform.

Automatic product copywriting for e‐commerce

AbstractProduct copywriting is a critical component of e‐commerce recommendation platforms. It aims to attract users' interest and improve user experience by highlighting product characteristics with textual descriptions. In this paper, we report our experience deploying the proposed Automatic Product Copywriting Generation (APCG) system into the JD.com e‐commerce product recommendation platform. It consists of two main components: (1) natural language generation, which is built from a transformer–pointer network and a pretrained sequence‐to‐sequence model based on millions of training data from our in‐house platform; and (2) copywriting quality control, which is based on both automatic evaluation and human screening. For selected domains, the models are trained and updated daily with the updated training data. In addition, the model is also used as a real‐time writing assistant tool on our live broadcast platform. The APCG system has been deployed in JD.com since February 2021. By September 2021, it has generated 2.53 million product descriptions, and improved the overall averaged click‐through rate (CTR) and the conversion rate (CVR) by 4.22 and 3.61%, compared to baselines, respectively, on a year‐on‐year basis. The accumulated gross merchandise volume (GMV) made by our system is improved by 213.42%, compared to the number in February 2021.

The Impact of the 6 P's on Motivating Egyptian Consumer to Purchase Online

This paper aims to detect the factors that motivate Egyptian consumers to purchase online and examine the impact of demographic characteristics on this matter. Six factors are suggested to be evaluated in this research, which are: product price, product variety, product quality, product description, product delivery, and promotion. The researcher named these suggested factors by the '6P's factors'. The researcher used the quantitative approach to collect data from 300 respondents. The sample covered a wide range of consumers in Alexandria city, Egypt who have awareness of online purchase. To analyze the collected data, correlation analysis, stepwise regression, two independent samples t-test, and One-Way ANOVA were used. The importance of this research lies in the fact that it will increase the familiarity of e-retailers with the factors that motivate Egyptian consumers to purchase online and thus work to improve the factors of higher relative importance. Also, it enables Egyptian marketing managers to adopt the appropriate marketing strategies that increase the satisfaction for Egyptian consumers toward the electronic service provided. The study concluded that there is a positive correlation between all the proposed factors and Egyptian consumer's intention toward online purchase but with varying degrees in terms of correlation strength. Furthermore, the results revealed that the Egyptian consumer's intention to purchase online is influenced also by gender, age, and educational level.

Способы повышения эффективности производственного контроля

The article focuses on the main shortcomings of production control at hazardous production facilities and on practical methods of improving the effectiveness of production control including methods determining the main causes of deviations in the production process from the safety standards, developing measures to eliminate the deviations and ensuring the observance of such measures. The cases of activating the production control at the hazardous industrial facilities have been shown, a new approach to observing the production control has been reasoned, a universal algorithm for implementing production control at hazardous production facilities has been developed. Improving the operating principles of production control can be realized through the introduction of new control tools. One of them is a checklist of patterns of emerging a hazardous production situation, which allows to make a score evaluation of the danger. The main elements for implementing the developed algorithm and checklist into the production process are considered. There are shown the main structural elements of formulating a technical task for writing a program code: setting a project goal, substantiating the project budget, listing the specific works, description of the final product, required result, deadlines, and future maintenance costs.

Anomalous Higgs boson couplings in weak boson fusion production at NNLO in QCD

The production of Higgs bosons in weak boson fusion has the second largest cross section among Higgs-production processes at the LHC. As such, this process plays an important role in detailed studies of Higgs interactions with vector bosons. In this paper we extend the available description of Higgs boson production in weak boson fusion by considering anomalous $HVV$ interactions and NNLO QCD radiative corrections at the same time. We find that, while leading order QCD predictions are too uncertain to allow for detailed studies of the anomalous couplings, NLO QCD results are sufficiently precise, most of the time. The NNLO QCD corrections alter the NLO QCD predictions only marginally, but their availability enhances the credibility of conclusions based on NLO QCD computations.

Industrial Production of Proteins with Pichia pastoris-Komagataella phaffii.

Since the mid-1960s, methylotrophic yeast Komagataella phaffii (previously described as Pichia pastoris) has received increasing scientific attention. The interest for the industrial production of proteins for different applications (e.g., feed, food additives, detergent, waste treatment processes, and textile) is a well-consolidated scientific topic, and the importance for this approach is rising in the current era of environmental transition in human societies. This review aims to summarize fundamental and specific information in this scientific field. Additionally, an updated description of the relevant products produced with K. phaffii at industrial levels by a variety of companies-describing how the industry has leveraged its key features, from products for the ingredients of meat-free burgers (e.g., IMPOSSIBLE™ FOODS, USA) to diabetes therapeutics (e.g., Biocon, India)-is provided. Furthermore, active patents and the typical workflow for industrial protein production with this strain are reported.

AAfrag 2.01: interpolation routines for Monte Carlo results on secondary production including light antinuclei in hadronic interactions

Light antinuclei, like antideuteron and antihelium-3, are ideal probes for new, exotic physics because their astrophysical backgrounds are suppressed at low energies. In order to exploit fully the inherent discovery potential of light antinuclei, a reliable description of their production cross sections in cosmic ray interactions is crucial. We provide therefore the cross sections of antideuteron and antihelium-3 production in pp, pHe, Hep, HeHe, p¯p and p¯He collisions at energies relevant for secondary production in the Milky Way, in a tabulated form which is convinient to use. These predictions are based on QGSJET-II-04m and the state of the art coalescence model WiFunC, which evaluates the coalesence probability on an event-by-event basis, including both momentum correlations and the dependence on the emission volume. In addition, we comment on the importance of a Monte Carlo description of the antideuteron production and on the use of event generators in general. In particular, we discuss the effect of two-particle momentum correlations provided by Monte Carlo event generators on antinuclei production. Program summaryProgram Title:AAfrag 2.01CPC Library link to program files:https://doi.org/10.17632/6f73jz6jx8.2Developer's repository link:https://aafrag.sourceforge.ioCode Ocean capsule:https://codeocean.com/capsule/1159734Licensing provisions: CC BY-NC 4.0Programming language: The program exists both in a Python 3 and Fortran 90 versionJournal reference of previous version: Comp. Phys. Comm. 245, 106846 (2019)Does the new version supersede the previous version?: YesReasons for the new version: Inclusion of antinuclei tables, and a Python 3 version for the pedestrian.Summary of revisions: Improved formatting of tables, inclusion of new secondaries, inclusion of Python version.Nature of problem: Calculation of secondaries (photons, neutrinos, electrons, positrons, protons, antiprotons, antideuterons and antihelium-3) produced in hadronic interactions.Solution method: Results from the Monte Carlo simulation QGSJET-II-04m are interpolated.

The Worthwhileness of Immersive Journalism—Taking on an Audience Perspective

ABSTRACT A growing number of studies in journalism research are concerned with the effects of immersive journalism (IJ) on audience perceptions and behaviors. This interest in IJ is logical, because IJ has the potential to become an impactful innovation for the industry. However, we have largely neglected the question of whether audiences want this form of emotional journalism. This study fills this gap and investigates whether people consider IJ worth their while. Using a factorial survey design, we presented a sample of 2000 German citizens with descriptions of an immersive production about protests in Belarus, in which we manipulate the use of inclusive technology (VR vs. AR vs. video), immersive narratives (first person vs. third person), agency (choice of perspective vs. no choice of perspective and control of location vs. no control), and emotionality (positive vs. negative vs. neutral tone). The analyzes reveal that an immersive narrative perspective, control and emotionality do not predict worthwhileness perceptions. However, productions that present people with inclusion and technological agency render this production more worthwhile in the eye of the individual user.

Hybrid meat products and co-creation: What do consumers say, feel and think?

What consumers say about food and what kind of words they use to do so offers direct insights into their perceptions, preferences, reasoning, and emotions. This study explores evaluations of hybrid meat products of 2,405 consumers from England, Denmark, and Spain. As part of a large survey, consumers were prompted to note down four words that come to mind when they read a description of a hybrid meat product, and then again after they were involved in a hypothetical co-creation task of a hybrid meat product. 18,697 words and phrases of language material was processed using computational corpus-based analysis and manual classification into semantic categories including: Evaluation, Sensory, Production, Emotion, Diets, Quality, Ethics, and Other. Consumers consider many dimensions when it comes to the evaluation of hybrid meat products including ethical conduct and sustainability. For all three languages, the number of positive words increased and the number of negative words decreased significantly (p < 0.001) following the co-creation task, suggesting that consumers see such products very positively once they are more familiar with them and know more about the ingredients. Subcategories that received most words include: taste, ingredients, healthiness, naturalness, innovation, and environment, implying that these areas are of most importance when it comes to the evaluation of hybrid meat products. The concept of nutrition (especially words pointing to positive aspects such as "rich in vitamins", "nutritious") also rose significantly in use after co-creation. The study reveals consumers' vocabulary of hybrid meat products across the three countries and offers important insights for food producers to help them create innovative products that better align with consumers' perceptions and expectations.

Basic Principles of Secure Information Systems

The relevance of the work lies in the fact that the pace of development of the field of information security does not correspond to progress in the development of data processing methods, resulting in a serious lack of practical knowledge of the subject area, which prevents the creation of conditions for secure recording, processing and storage of data. In the process of writing the article, modern methods and principles of ensuring information security, including a mandatory approach, were studied, and a brief description of software products supporting this approach was given. The mandatory method of information protection implies granting access rights to certain actions in accordance with the user’s status. Such actions can be, for example, writing, reading and changing data. Examples of user statuses are ‘administrator’ and ‘reader’, where the administrator, as a rule, is provided with the entire list of available actions, and the reader is provided with only a minimum, sufficient for familiarization activities. In its architecture, the mandatory approach often contains tools for conducting cluster analysis. Cluster analysis can be used both to carry out work on risk analysis and assessment, and to determine the degree of protection of an object. In any case, when building a cluster, it should be taken into account that some levels of protection may be represented by more objects than others. There are software products on the information security market that allow the use of a mandatory method of ensuring information security. One of the striking examples is the PostgreSQL database management system, which has an apparatus of labels assigned according to the user’s level of rights: the higher the level of rights, the higher the access level.

ChatGPT: Exploring the Role of Cybersecurity in the Protection of Medical Information

ChatGPT is a large language model developed by OpenAI. It is trained on a dataset of conversational text and can be used to generate human-like responses to prompts in a variety of languages and formats. It can be used for tasks such as chatbots, language translation, and text completion. The role of ChatGPT is to generate human-like text based on a given prompt or context. It can be used in a variety of applications such as chatbots, language translation, text completion, and question answering. Additionally, it can be fine-tuned for specific tasks such as generating product descriptions or summarizing articles. It can also be used to generate creative writing such as poetry and stories. It can be integrated into a wide range of industries from customer service to entertainment, to research.

Composition of Flavour Non Volatile Compound Steamed Milkfish (Chanos chanos)

The purpose of this study is to identify the composition of non-volatile flavor compounds contained in steamed milkfish (Chanos chanos). This study was carried out at the Fisheries Product Processing Laboratory, Faculty of Fisheries and Marine Sciences, Padjadjaran University, Jatinangor; IPB Integrated Laboratory. The study was conducted experimentally by treating a sample of 100 grams of steamed milkfish (at 100°C for ± 30 minutes) to identify non-volatile compounds and 1 milkfish to test the description. Product description tests were carried out on samples which included appearance, flesh, aroma, texture, and taste. High Performance Liquid Chromatography (HPLC) was used to identify non-volatile flavour compounds. The findings revealed that steamed milkfish had 15 non-volatile flavor compounds identified from 15 amino acid compounds. The two umami-flavoring amino acids are 3.21% glutamic acid and 2.14% aspartic acid. The four sweet tasting amino acids are 1.31% alanine, 0.96% threonine, 1.13% glycine and 0.72% serine. The nine bitter amino acids are lysine 2.15%, leucine 1.74%, arginine 1.32%, valine 1.26%, isoleucine 1.16%, phenylalanine 0.95%, tyrosine 0.79%, methionine 0. .69% and 0.90% histidine. Steamed milkfish has a whole appearance with a bright yellowish color. The savory aroma of fresh steamed milkfish is in accordance with the characteristics of milkfish that live in brackish water. The texture of the meat is dense and very dense. The taste of savory steamed milkfish is according to its kind.

Modeling the effect of glucagon on endogenous glucose production in type 1 diabetes: On the role of glucagon receptor dynamics

This paper validates a glucoregulatory model including glucagon receptors dynamics in the description of endogenous glucose production (EGP). A set of models from literature are selected for a head-to-head comparison in order to evaluate the role of glucagon receptors. Each EGP model is incorporated into an existing glucoregulatory model and validated using a set of clinical data, where both insulin and glucagon are administered. The parameters of each EGP model are identified in the same optimization problem, minimizing the root mean square error (RMSE) between the simulation and the clinical data. The results show that the RMSE for the proposed receptors-based EGP model was lower when compared to each of the considered models (Receptors approach: 7.13±1.71 mg/dl vs. 7.76±1.45 mg/dl (p=0.066), 8.45±1.38 mg/dl (p=0.011) and 8.99±1.62 mg/dl (p=0.007)). This raises the possibility of considering glucagon receptors dynamics in type 1 diabetes simulators.

Sentiment enhanced answer generation and information fusing for product-related question answering

The reviews written by users in E-commerce platform have been fully exploited by product-related question answering systems, which ignore the product descriptions with valuable information to improve the system performance, especially for objective questions. In this paper, we propose a model named as Sentiment-enhanced Answer Generation and product Descriptions Fusing (SAGDF) for Product-related Question Answering task. The valid information from user reviews and product descriptions are learned jointly for answer generation. Importantly, the sentiment analysis task is performed initially to make the model judge the sentiment tendency correctly for answer accuracy. The review encoder of the model is fine-tuned on the large-scale Amazon review dataset to implement the sentiment analysis task. In addition, we build the dataset named AmazonQARD and it contains both reviews and corresponding product descriptions. The proposed model is trained on AmazonQARD and it processes user reviews individually and integrates product descriptions to constantly correct the generated answers iteratively. Experimental results demonstrate that SAGDF significantly outperforms the other baseline systems.

A Linked Open Data–Based Terminology to Describe Libre/Free and Open-source Software: Incremental Development Study

There is a variety of libre/free and open-source software (LIFOSS) products for medicine and health care. To support health care and IT professionals select an appropriate software product for given tasks, several comparison studies and web platforms, such as Medfloss.org, are available. However, due to the lack of a uniform terminology for health informatics, ambiguous or imprecise terms are used to describe the functionalities of LIFOSS. This makes comparisons of LIFOSS difficult and may lead to inappropriate software selection decisions. Using Linked Open Data (LOD) promises to address these challenges. We describe LIFOSS systematically with the help of the underlying Health Information Technology Ontology (HITO). We publish HITO and HITO-based software product descriptions using LOD to obtain the following benefits: (1) linking and reusing existing terminologies and (2) using Semantic Web tools for viewing and querying the LIFOSS data on the World Wide Web. HITO was incrementally developed and implemented. First, classes for the description of software products in health IT evaluation studies were identified. Second, requirements for describing LIFOSS were elicited by interviewing domain experts. Third, to describe domain-specific functionalities of software products, existing catalogues of features and enterprise functions were analyzed and integrated into the HITO knowledge base. As a proof of concept, HITO was used to describe 25 LIFOSS products. HITO provides a defined set of classes and their relationships to describe LIFOSS in medicine and health care. With the help of linked or integrated catalogues for languages, programming languages, licenses, features, and enterprise functions, the functionalities of LIFOSS can be precisely described and compared. We publish HITO and the LIFOSS descriptions as LOD; they can be queried and viewed using different Semantic Web tools, such as Resource Description Framework (RDF) browsers, SPARQL Protocol and RDF Query Language (SPARQL) queries, and faceted searches. The advantages of providing HITO as LOD are demonstrated by practical examples. HITO is a building block to achieving unambiguous communication among health IT professionals and researchers. Providing LIFOSS product information as LOD enables barrier-free and easy access to data that are often hidden in user manuals of software products or are not available at all. Efforts to establish a unique terminology of medical and health informatics should be further supported and continued.

Analisa Bonus Demografi Dengan Algoritma Machine Learning Di Kabupaten Gorontalo Utara

Nationally, Indeks has entered the demographic bonus era since 2012 and is predicted to end in 2037. The demographic Bonus is the period during which 100 productive people are dependent on the unproductive population of a country below 50. The results of the 2020 population census recorded that the population in Gorontalo province reached 1,171,681 people, a data source from the Central Statistics Agency (BPS) of Gorontalo province. Not increasing opportunities in such a rapid digital era makes employment decline, especially in labor-intensive activities. On the other hand, the advancement of information technology opens up many new business opportunities. This is the challenge of this nation in welcoming the demographic bonus. Demographic Bonus in Gorontalo. The problem of the impact of the demographic bonus in addition to the ongoing covid 19 pandemic also holds many problems that will also have an impact on uneven economic recovery, unemployment,stunting, and poor nutrition. The government’s efforts to overcome and control population growth have had an impact on changes in the demographic structure of the population in Gorontalo. The purpose of this study is to produce a product description of knowledge pattern analysis of population data in the province of North Gorontalo from data extraction with machine learning algorithms. Clustering analysis, the experimental results with K-Means model k value with the best bouldin indeks feature is at K=3, for classification analysis with decision tree model of the demographic dataset of North Gorontalo region has an accuracy of 89.29% while using the random forest model reaches 100% accuracy.