Reviewerly/exHarmony huggingface dataset:
Contribution of scanner in the breast cancer extension assessment in the radiology department of CNHU-HKM in Benin

Introduction: Breast cancer is the most common female cancer in the world.The prognosis depends on whether metastasis is present or not.The objective of this study was to provide an overview of the CT scan aspects identified during the evaluation of breast cancer extension in the Radiology department of the Teaching University Hospital of Hubert Koutoukou Maga (CNHU-HKM) in Cotonou in Benin.Materials and Methods: It was a descriptive study with retrospective collection, conducted from January 1, 2018 to January 31, 2019 (13 months), in the Radiology department of CNHU-HKM.It focused on patients referred for a chest-abdominal-pelvic computed tomography (PET) scan, as part of an extension assessment for breast cancer.Results: During the period of the study, 40 chest-abdominal-pelvic CT scans were compiled, of which 38 (95%) were women and 02 men (5%), and among which 23 were metastatic, accountings for a prevalence of 57.5%.The average age was 51.22  16.33 with extremes of 30 and 83 years old.Among our patients, 32 (80%) had undergone a CT scan for an initial diagnostic of extension assessment, and 08 (20%) for the therapeutic response assessment.According to the TNM classification, T4 tumors accounted for 27.5% (11 cases).Lymph node involvement was found in 18 cases (43.90%), accounting for 12 (30%) of N1 and 6 (15%) of N3.The most commonly found metastatic sites were the lung in 25% followed by the pleura and the liver with equal percentages (10%).The metastases CT scan aspect was typically a carcinomatous lymphangitis appearance; fluid pleural effusions; hypodenses hypovascular nodules hepatics; osteolytic or mixed bone damage and peritoneum, especially fluid effusion associated with peritoneal nodules. Conclusion:The frequency of breast cancer metastases is high in Benin.The most commonly found metastatic sites on scanner in descending order are the lungs, liver and bones.
PENERAPAN MEDIA PEMBELAJARAN BoneLab UNTUK MENINGKATKAN HASIL BELAJAR PESERTA DIDIK

This study aims: 1) to find out the increase in student learning outcomes; and 2) to find out students' responses after applying BoneLab learning media in class VIII at MTs. Nahdlatul Mujahidin NW Jempong. The research method uses Classroom Action Research (CAR), which consists of 2 cycles, each cycle containing the stages of preparation, implementation, observation, and reflection. The research instruments consisted of: 1) teacher observation sheet activity; 2) student observation sheet activity; 3) learning achievement test sheets; and 4) student questionnaire response sheets. The data analysis technique used is quantitative descriptive analysis with percentages. The results of the study stated that, the activities of teachers in the first cycle carried out "very well" with an average percentage of 86.48%. Whereas in the second cycle, it performed "very well" with an average percentage of 89.60%, an increase of 3.12%. Activities of students in the first cycle, the average percentage obtained was 89.30% with the category "very good". While in cycle II, the average percentage obtained was 91.5% with the category of "very good", an increase of 2.2%. The percentage of the number of students experiencing mastery learning outcomes of students in the first cycle was 46%, and in the second cycle was 66%. The percentage of students' responses to learning is 82.8%.
The impact of COVID-19 pandemic-Entrepreneurial Uncertainty and Effect on Economic Development

This paper illustrates however chronic uncertainty caused by crisis events affects the provision of entrepreneurial sources of finance for starts -ups and tiny and medium sized enterprises (SMEs).To explore this line of argument, this paper examines crunch base period knowledge examining entrepreneurial finance investments in China throughout development COVID-19 crisis.The paper shows that these equity investments unerect dramatically within the immediate aftermath of COVID-19 virus, leading to a year on year decrease of 60% within the total volume of investment raised between quarter one in 2019 and quarter 1 in 2020.Importantly, the paper found early-stage seed investments falling the steepest, suggesting aborning starts-ups are those most heavily affected by the crisis.Overall, enterprise policy manufacturers have to be compelled to become higher attuned at watching period of time data sources to mitigate chronic entrepreneurial uncertainty via strategic policy responses.
The Influence of Index Card Match Learning Models on Motivation And Learning Outcomes in Class V IPS Lesson / Pengaruh Model Pembelajaran Index Card Match terhadap Motivasi dan Hasil Belajar pada Pelajaran IPS Kelas V

The convesional model that was previously applied in class V MIN 33 Aceh Besar so that it makes students less active in participating in social studies learning schingga change the pattern by applying the Index Crad Macth learning model. This study aims to explain the effect of the application of the Index Card Match learning model on student motivation and learning outcomes in the social studies subject for class class V MIN 33 Aceh Besar. The type of this research is qualitative based on facts or events systematically and accurately. The data collection technique was carried out by interviewing respondents namely 2 (two) Social Studies teachers in Class V and 1 (one) informant, namely the Principal at MIN 33 Aceh Besar. The results showed that the application of learning methods with the Index Card Match system could increase student motivation in social studies subjects in class V MIN 33 Aceh Besar, this can be seen from the higher level of student activity. The final score show that the learning outcomes of students also increase, this is can be seen from the point of value, creativity, cognitive, affective and psyhological abilities that achieve KKM completeness with a mean value of this study is that the Index Card Match learning model has an effect on the motivation and learning outcomes of students in sosial studies.
Effective system for software requirement management

In software engineering, requirements analysis comprises of those tasks that are necessary to encounter a novel or an improvised one, by considering the possible contradictoryrations of the various stakeholders, analyzing, documenting, and managing the requirements. Requirements engineering for software development process is a complex exercise which considers product demands from various viewpoints, roles, responsibilities, and objectives. Hence, it is important to incorporate requirement engineering practices in every stage of software development process. In this paper, we propose an effective requirements engineering process model that prioritizes functional and non- functional requirements and createeminence requirements for software development. The successful implementation of the proposed process delivers a high quality software product.
Management Strategy Scheme Based on Ocean Big Data Information

Hu, X.; Zhong, W.J., and Cheng, J., 2020. Management strategy scheme based on ocean big data information. In: Li, L. and Huang, X. (eds.), Sustainable Development in Coastal Regions: A Perspective of Environment, Economy, and Technology. Journal of Coastal Research, Special Issue No. 112, pp. 319-321. Coconut Creek (Florida), ISSN 0749-0208.With the development of international ocean shipping and the huge amount of ocean data, how to effectively and scientifically carry out marine data information management has become an urgent problem to be solved. Based on this, this paper first studies the current situation and trend of marine data management based on ocean big data information. Secondly, it analyzes the key technologies of ocean management platform based on ocean big data information, and analyzes the problems and needs of ocean big data information management. Finally, it gives the strategy scheme of ocean data information management based on big data.
When the Invented Becomes the Inventor: Can, and Should AI Systems be Granted Inventorship Status for Patent Applications?

Artificial Intelligence (“AI”) systems have become vastly more sophisticated since the term was first used in the 1950s. Through the advent of machine learning and artificial neural networks, computers utilizing AI technology have become so advanced that a team of attorneys in the United Kingdom claim that their AI machine, DABUS, actually created patentable inventions. The team went so far as to file patent applications with the European Patent Office,the UK Intellectual Property Office, and the US Patent and Trademark Office. All applications named DABUS as the inventor. This sparked a heated debate within academic and legal communities that centered around whether AI can be an inventor, and, if so, what this might mean for the current state of patent law. This paper discusses the purposes of patent law through a brief look at its history, in an effort to highlight why patent law as it stands may no longer be one- size-fits-all. It considers the evolution of AI systems to explain how one might determine that a machine could be “creative” and therefore justifiably named as inventor. It surveys popular opinions and organizes them on a spectrum ranging from those who believe that patent law should stay as it is and that AI cannot be an inventor, to those who, more dramatically, advocate for the abolition of patent protection for AI inventions. This paper suggests that legislators be proactive in traversing this technological minefield rather than reactive, as technology will continue to outpace, and trample, law if left to its own machinations.
In-Silico Screening: Accurately Predicting Results of the Direct Antiglobulin Test using Commonly Available Lab Data

Abstract Introduction/Objective The Direct Antiglobulin Test (DAT) is a useful screening test to determine whether a patient’s red blood cells have been sensitized to immunoglobulin or complement. Like the majority of screening tests, the DAT compromises specificity for sensitivity in order to quickly assess for hemolysis and its dangerous sequelae. Because of the high sensitivity of the DAT, improper ordering of this test can confuse the clinical picture at best and result in misdiagnosis at worst. Pre-tests for ruling-out disease have proven effective in limiting test ordering, such as the Pulmonary Embolism Rule-out Criteria (“PERC rule”) for limiting the use of D-dimers. A similar pre-test could prove useful in DATs. We use “in silico testing” – testing via computer simulation – to predict the likelihood of any DAT being positive, given common patient attributes and laboratory values. Methods A three-layer deep-learning artificial neural network (ANN) was created using Python and the machine learning framework Keras. The ANN was compiled to maximize specificity while retaining 100% sensitivity. Input variables to the model were patient sex and age, along with most recent lab values for hemoglobin, hematocrit, white blood cell count, platelet count, total bilirubin, direct bilirubin, and haptoglobin, where available. The output of the ANN was a binary variable: “ruled-out” versus “further testing necessary”. The ANN was trained on all positive (n=30) and negative (n=63) DATs performed on November 2019 through March 2020, with a final total of ninety-three patients. A 10-fold cross-validation of the entire dataset was used to measure performance. Results The ANN was able to maximize specificity to 83% while retaining 100% sensitivity. A ROC curve of the model shows performance well above that of the no-discrimination line. Conclusion “In-silico testing” can accurately screen the likelihood of a positive result for a labor and time-intensive test, such as the DAT, before the actual test is performed. This has the potential to reduce unnecessary testing if validated in clinical practice. Analogous to their clinical counterpart “the PERC rule,” computer models that maximize specificity while retaining 100% sensitivity could achieve more effective test utilization and more informative results.
The context account does not explain why remembering some pictures leads to forgetting others

When we access a visual long-term memory representation, one of the unintended consequences is that we forget related representations. What is driving this forgetting? One theoretical explanation for this phenomenon is that there is a shift in context during these experiments, driving the forgetting effect. This explanation hinges on the fact that in previous experiments demonstrating this forgetting effect, the exposure to pictures of objects unfolds across three phases. In the first phase the objects are studied, in the second phase some items are shown again in an old-new recognition judgment task, and in the third phase visual long-term memory for all the pictures is tested. The context account argues that during the third and final test phase, people activate the context of the second phase to search their memory, because is the most temporally recent context. This contextual activation during the third test phase causes problems remembering the items shown only during the first study phase. The context account makes the clean prediction that if the first phase were reactivated, the apparent effects of forgetting should disappear. Thus, we created distinct contexts for the study and practice phases, either of which could then be reactivated at test. Across two experiments we found reliable forgetting effects, regardless of which context was activated. These results challenge contextual theoretical accounts of the forgetting of visual long-term memory representations.
PIT LibGuides: Library Home: Contact-Free Circulation

Welcome to the Pennsylvania Institute of Technology's Library online guide. COVID-19 Library Services
Social Risks Of University Administration In Personnel Assessments

The article considers the transformation of modern universities into specific corporations ("quasicorporations") with the following characteristics: a clear statement of the mission; active involvement in entrepreneurial activity with the help of production and transfer of innovative products to interested public entities on a reimbursable basis; modification of interaction with the external environment through the exchange of goods and services; creation of flexible network structures focused on consumer needs.It is proved that the "corporatization" of universities contributes to the widespread use of administrative management practices.Their features are: branched and hierarchically built managerial (administrative) apparatus; regulation and formalization of activities; widespread use of penalties and sanctions, focused on coercion; emphasis on developing and maintaining a corporate culture.It is proved that the expansion of administrative management practices within the framework of the traditional university environment leads to the set of risks connected with a possibility of not achieving aims of scientific and educational process.Based on the results of universities of the Belgorod region in 2018-2019, dispositions of main groups of university staff in relation to risks are determined.Despite the recognition of defects in the administrative management system, it is shown that the feeling of satisfaction with them is typical for most of the university staff.The risk is usually perceived in a negative sense and identified with the threat, which minimizes the likelihood of using the positive opportunities followed by the risks.It also does not contribute to building an effective risk management strategy.
Verimlilikte Yapay Zeka’nın Rolü: Şarap Kalitesinin Tahminine Yönelik Bir Vaka Çalışması

Artificial intelligence has been used in many areas in recent years and has achieved quite successful results. Like using artificial intelligence from healthcare to driverless vehicles, it also has often been used to increase productivity in the production sector. In this study, we tried to draw a framework for the use of artificial intelligence algorithms in a data set that is not normally distributed. Any artificial intelligence algorithm can be easily applied on normally distributed data sets, while data sets that do not normally distributed require a different operation to the data itself or it is necessary to revise the theoretical structure of the algorithm. In this regard, three different methodologies are applied in this study. Initially, Support Vector Machines, which are often used in the literature, is used. In addition, Weighted Support Vector Machines, which is the revised version of the Support Vector Machines to produce successful results in abnormal distributed data sets. Finally, the Synthetic Minority Oversampling Technique (SMOTE) is applied and the data set used was artificially converted to normal distribution. Three techniques are compared in terms of sensitivity, specificity, precision, prevalence, F-1 score, and G-Mean evaluation criteria were compared. According to the results of the study, Weighted Support Vector Machines produced the most successful results according to the evaluation criteria used.
REMINDER - Register Now: Online Workshop on the Use of High-accuracy Coordinate Track Adjustment Systems for Greater Efficiency of Existing Infrastructure – UIC Communications

At the initiative of RZDStroy and supported by RZD, UIC is pleased to invite you to an online workshop on the use of high-accuracy coordinate track adjustment systems for greater efficiency of…
Improved Water Cycle Algorithm and K-Means Based Method for Data Clustering

K-means is a classical clustering method, but it is easy to fall into local optimums because of poor centers. Inspired by the good global search performance of Inter-Peer Communication Mechanism Based Water Cycle Algorithm (IPCWCA), three hybrid methods based on IPCWCA and K-means are presented in this paper, which are used to address the shortcoming of K-means and explore better clustering approaches. The hybrid methods consist of two modules successively: IPCWCA module and K-means module, which means that K-means module will inherit the best individual from IPCWCA module to start its clustering process. Compared with original K-means and WCA + K-means methods on eight datasets (including two customer segmentation datasets) based on SSE, accuracy and Friedman test, proposed methods show greater potential to solve clustering problems both in simple and customer segmentation datasets.
ANALYSIS OF DESIGN AND IMPLEMENTATION OF INFORMATION SYSTEM OF LIBRARY OF UIN SUNAN KALIJAGA JOGYAKARTA

&lt;p&gt;The purpose of writing this article is to find out how to design and implement the Information System of the Sunan Kalijaga State Islamic University Yogyakarta Library which is supported by the System Development Life Cycle (SDLC). The method used in this study is the type of field research that is "field research" which has the nature of skin research and data collection techniques with direct observation and information obtained through documentation in the field. The results and discussion in this article show that CYPRUS (Library Information System) has the task of collecting, processing, preserving, reinventing information, borrowing and returning books in the circulation section, already using information technology to store data and library collections, in the design process This library information system also uses the MySQL database in streamlining the library information system, and from the plan, it can be used by the admin and librarian and the results are shown in the library information system design show that there is data collection on the members, login columns, member data types, display reports free library, and display collection returns and borrowing columns.&lt;/p&gt;&lt;p&gt;Design and Implementation, Library Information System.&lt;/p&gt;
Analisis Banjir Sub DAS Cilemer HM 0+00 – HM 53+00

Rivers as natural water sources provide benefits for human life, flora, and fauna. The river is also a natural drainage channel to prevent flooding if it is managed properly. Most of the rainwater that falls to the land surface, flows to lower places due to gravity and eventually overflows into lakes or the sea. Along with changing conditions in the river basin, changes in land use and population growth have made the river not function optimally as it should have, causing flood disasters. A flood is an event of river water overflowing beyond the riverbed or standing water that occurs in low and non-drainable areas (SNI 2415: 2016). The purpose of this study was to determine the areas affected by the flood of the Cilemer River in Pandeglang Regency at HM 00 + 00 to HM 53 + 00, which can then produce policy recommendations in flood prevention so that the objectives are maximally achieved. Research supporting data was obtained from the Banten Province Water Resources Management Center. The analysis was carried out with several tests and the MAF method (Mean Annual Flood), process data using HEC-RAS 5.0.3, and ArcGIS 10.2.2 software. The results showed that the Cilemer River area HM 35 + 00 to HM 53 + 00 experienced flooding because the existing reservoir could not accommodate the planned discharge of 210.617 m3/s in Pagelaran and Patia areas, Pandeglang Regency.
Membrane filtration simulation study with variation in the number of filters on peat water media

The rapid population growth has an impact on the increasing need for drinking water. In swamp areas, the need for drinking water cannot be met immediately because it still contains organic compounds that make the water unfit for consumption. Peat water contains dissolved organic compounds that cause the water to turn brown and have an acidic character, so it needs special processing before it is ready for consumption. For peat water to be used by the community for drinking water, it is necessary to find an easy and cheap way to treat peat water. The use of a filtration device is one of the solutions that must be done in peat water treatment. The purpose of this study was to determine the effect of flow patterns, speed, and pressure on the filtration process with variations in the type of membrane and filtration arrangement. This research method was carried out by simulation using ANSYS 14.5 series. The simulation process begins with designing a filtration device with the following types: two-filter, three-filter, and four-filter. Then the simulation was performed by entering the value of the peat water properties into the regulatory equation.The results of this study indicate that the collaboration of two membranes with different holes in type-2 and 3 filters produces a good filtration rate. However, in type-4 filters, the use of a similar membrane is highly recommended. This filtration rate is influenced by the presence of a cross-flow reversal (CFR) region that appears, when using different filtration membranes at low pressure it doesn't matter. However, in other cases of systems operating at high pressure, CFR that appears tends to decrease the filtration rate, this is because CFR inhibits the flow rate in the filtration process
Linear transformation codes: codes with a compact description and transpoliser codes

In this paper we define linear transformation codes, which provides a compact description to traditional codes. We divide them into ideal codes and multiplicative codes and show that the multiplicative codes are the more useful of the two. We relate them to linear and additive codes over non-commutative rings and show how to use the canonical orthogonals in each case to construct new codes. Extending on the specific examples of centraliser and twisted centraliser codes, we define a new family of codes, which we call transpoliser codes, that can be defined over the binary field without the restrictive upper bound on the minimum distance.