Reviewerly/exHarmony huggingface dataset:
METASTRONG: Stata module for estimating the proportion of true effect sizes above or below a threshold in random-effects meta-analysis

metastrong estimates evidence strength for scientifically meaningful effects in meta-analyses under effect heterogeneity (ie, a nonzero estimated variance of the true effect distribution) as proposed by Mathur and VanderWeele (2019; 2020). metastrong reports the estimated proportion of true effect sizes above or below a chosen threshold of a meaningful effect size q, together with confidence intervals derived via the bootstrap. These metrics could help identify if (1) there are few effects of scientifically meaningful size despite a “statistically significant” pooled point estimate, (2) there are some large effects despite an apparently null point estimate, or (3) strong effects in the direction opposite the pooled estimate also regularly occur (and thus, potential effect modifiers should be examined) (Mathur and VanderWeele 2019). By default, metastrong performs estimation using the method (Mathur and VanderWeele 2020) that extends work by Wang and Lee (2019). metastrong first calibrates the effect estimates and then computes the proportion of studies above (or below) q. This method makes no assumptions about the distribution of true effects and performs well in meta-analyses with as few as 10 studies. When the parametric option is specified, metastrong estimates the proportion of studies above (or below) q using the formulae devised by Mathur and VanderWeele (2019). This estimate is then bootstrapped to derive confidence intervals. As with the calibrated method, at least 10 individual studies should be available in the meta-analysis for these estimates to provide valid results. Point estimates produced by metastrong correspond to those produced by the function prop_stronger in the R package MetaUtility as of version 2.0.0. Confidence intervals will likely differ between packages given that Stata and R use different random number seeds for determining which studies to include in each bootstrap repetition.
Petrography, geochemistry and Fractal analysisof Mafic Enclaves in the Alvand Plutonicto investigate magma mixing processes

The Alvand plutonic complex is located in Sanandaj- Sirjan Zone in south and west of Hamedan. Petrographic studies indicate that this body is composed of mafic intrusive rocks, porphyry granitoids and leoucocratic granitoids with various enclaves such as surmicaceous, mafic microgranular and felsic microgranular enclaves. Field, petrography and geochemical studies show that enclaves, the host rock and mafic rocks have calc-alkaline affinity and aluminum saturation index of the host rock is peraluminous and mafic microgranular enclaves and mafic rocks are metaluminous and in the boundary between metaluminous and peraluminous field. On the basis of spider diagrams, all rocks are depleted in HFSE and enriched in LILE. which is particular of rocks of the subdution zones. The complexity of the morphology of the enclaves (fractal dimension) confirms the importance of magma mixing in this body. Fractal dimensions of the enclaves vary between 1.08 to 1.21 and the frequency of Dbox=1.1 is the highest one in histogram. According to the fractal dimensions of enclaves, the logarithm of viscosity ration of the host rock and the enclave ranges from 0.48 to 0.74 with most values clustering around 0.51. Since the microgranolar mafic enclaves in the Alvand Plutonic complex are seen in different forms, this suggests that the effect of magma mingling (mechanical mixing) on the enclaves and the host have been various in different parts of the Alvand body so that from border of mafic body to center of granitoid body enclaves become smaller and fewer; and their fractal dimensions decrease.
Graph Learning via Spectral Densification

Graph learning plays important role in many data mining and machine learning tasks, such as manifold learning, data representation and analysis, dimensionality reduction, data clustering, and visualization, etc. For the first time, we present a highly-scalable spectral graph densification approach (GRASPEL) for graph learning from data. By limiting the precision matrix to be a graph-Laplacian-like matrix in graphical Lasso, our approach aims to learn ultra-sparse undirected graphs from potentially high-dimensional input data. A very unique property of the graphs learned by GRASPEL is that the spectral embedding (or approximate effective-resistance) distances on the graph will encode the similarities between the original input data points. By interleaving the latest high-performance nearly-linear time spectral methods, ultrasparse yet spectrally-robust graphs can be learned by identifying and including the most spectrally-critical edges into the graph. Compared with prior state-of-the-art graph learning approaches, GRASPEL is more scalable and allows substantially improving computing efficiency and solution quality of a variety of data mining and machine learning applications, such as manifold learning, spectral clustering (SC), and dimensionality reduction.
Witness Protection: An Important Measure for the Effective Functioning of Criminal Justice Administration

The efficacy of criminal justice administration can be adjudged by the ability of courts to punish the wrongdoer and impart justice to the victim. During the process of finding the guilt, courts rely upon the evidence adduced by the parties in the oral or documentary form. The oral evidence is submitted by the means of versions of witnesses. Witness act as a valuable source of information for the courts to bring out the guilt of the accused. The versions of witness facilitate the courts to arrive at a judicious decision. Therefore, the witness plays a prominent role in criminal justice administration. For this reason, Whittaker Chambers said, “In search of truth, he plays that sacred role of the sun, which eliminates the darkness of ignorance and illuminates the face of justice, encircled by devils of humanity and compassion.” However, it is a bitter truth that the condition of witnesses is turning pathetic in the justice administration system day by day. The reports of inducement, threatening, harassment and intimidation of witnesses are coming every day on a rolling basis. All these incidences create fear in the mind of witnesses due to which witness hesitate to come forward to cooperate in the court process and often turn hostile. Moreover, a witness also falters due to lack of witness protection mechanism in our country. Law Commission of India in its various reports highlighted the problems faced by the witness during the course of the trial and recommended to incorporate a comprehensive policy on witness protection. Hon’ble Supreme Court of India through its judgement revamped the urge for witness protection regime in the Indian judicial system. In this research paper, the researcher seeks to highlight the problem faced by the witnesses in the criminal justice system and discuss the issue of witness protection in India.
USING TASKS TO FORM STUDENTS’ SYSTEMIC KNOWLEDGE IN GENERAL CHEMISTRY

The paper deals with the use of tasks as one of the important means of forming students’ systemic knowledge in general chemistry. The influence of the use of chemical tasks in teaching on the ability of students to establish various types of relationships that underlie the system of inter-conceptual connections is studied.
Menu Package Recommendation using Combination of K-Means and FP-Growth Algorithms at Bakery Stores: Menu Package Recommendation using Combination of K-Means and FP-Growth Algorithms at Bakery Stores

Bakery shop is a shop that sells variants menu like bread, cakes, and drinks. The main problem with this store's sales is still not knowing which product items are best sellers and the shop still markets a lot of non-selling menus, causing the shop to lose money. So it takes the right strategy to increase the sales of bakery shop menus by making a menu package recommendations from the menus most frequently purchased by customers. The k-means algorithm performs grouping on menus to get menu packages. Furthermore, the fp-growth algorithm looks for linkages between frequently purchased menus to get menu package recommendations. The results of the research that the dominant items often purchased in cluster0 packages are hotdogs, pancakes, milk, garlic breadsticks with a confidence value of 92%, cluster1 packages are garlic breadsticks, hotdogs, chicken sand, pancakes with a confidence value of 92% and the last cluster2 packages are garlic breadstick, pastry, milk with a confidence value of 79%.
Self-Supervised Learning for Code Retrieval and Summarization through Semantic-Preserving Program Transformations

Code retrieval and summarization are useful tasks for developers, but it is also challenging to build indices or summaries of code that capture both syntactic and semantic essential information of the code. To build a decent model on source code, one needs to collect a large amount of data from code hosting platforms, such as Github, Bitbucket, etc., label them and train it from a scratch for each task individually. Such an approach has two limitations: (1) training a new model for every new task is time-consuming; and (2) tremendous human effort is required to label the data for individual downstream tasks. To address these limitations, we are proposing Corder, a self-supervised contrastive learning framework that trains code representation models on unlabeled data. The pre-trained model from Corder can be used in two ways: (1) it can produce vector representation of code and can be applied to code retrieval tasks that does not have labelled data; (2) it can be used in a fine-tuning process for tasks that might still require label data such as code summarization. The key innovation is that we train the source code model by asking it to recognize similar and dissimilar code snippets through a \textit{contrastive learning paradigm}. We use a set of semantic-preserving transformation operators to generate code snippets that are syntactically diverse but semantically equivalent. The contrastive learning objective, at the same time, maximizes the agreement between different views of the same snippets and minimizes the agreement between transformed views of different snippets. Through extensive experiments, we have shown that our Corder pretext task substantially outperform the other baselines for code-to-code retrieval, text-to-code retrieval and code-to-text summarization tasks.
Pengalaman Adaptasi Antarbudaya Mahasiswa Perantau di Kota Kupang

This study aims to describe the communication experience of Manggarai students when adapting to students from Kota Kupang at Nusa Cendana University and to analyze the strategies / stages that students go through and to find out and analyze the meanings of Manggarai students about the status of migrant students in Kupang City. This study uses the phenomenology method with the reason that this research departs from phenomena or experiences that occur in everyday life. By using potential informants as data sources, in this study the data is presented through in-depth interviews and non-participant observation. The data analysis technique used is data reduction, data presentation, and conclusions / verification. This study uses the Accommodation Theory of Communication and Phenomenology Theory as a reference for data analysis. The results of the study based on the Communication Accommodation Theory that from communication experience revealed that, students from Manggarai who were studied conducted convergence by learning to use the dialect and the Kupang language. This is done in order to create effective communication where, the mutual understanding between communicators and communicants. Not only that, students from Manggarai also began to build social intimacy with Kupang City students. In addition, the form of strategies / stages of cultural adaptation carried out by students from Manggarai are students from Manggarai studied doing strategies or stages classified in the Readjustment stage (adaptation phase), and Resolution (resolution / adjustment phase), based on resolution or the final results carried out by Manggarai students were, full participation, where they began to be friends with Kupang City students, and acted as if they were students from Kupang City. Finally, the meaning of students from Manggarai about the status of migrant students in Kota Kupang is based on the Phenomenology Theory in which the knowledge underlying the meaning is obtained through direct experience of students from Manggarai, namely: migrant students as change makers for a better life in the future, and migrant students as science fighter.
Internet Users in Damanhur’s Town, Characteristics, Problems, and Spatial Variability.

Abstract The aim of the study was to identify the factors influencing the use of internet in Damanhur town, analyzing population demographic, economic and social characteristics, and identifying levels of satisfaction with the network and its positive and negative aspects. The study adopted the analytical inductive approach which detailing and clarifying the phenomenon of internet users to reach the desired results, it also relied on SPSS for many statistical and cartographic methods. The study resulted in several results, which were: - Age group (15, less than 30 years old) has the highest internet penetration rate in town. - High percentage of low-income network users. - The use of the network through social networking sites at the top of the reasons for use. - Most users were satisfied with the cost and efficiency of internet, despite the multitude of problems. - Continuation of the sample of the study in the use of internet, despite the problems that may be. Key Words: Internet users, population satisfaction, Damanhur town.
LA INVESTIGACIÓN EN EDUCACIÓN PATRIMONIAL. EXPERIENCIAS DESDE EL MOBILE LEARNING EN UN CONTEXTO UNIVERSITARIO

In recent decades, through the resounding irruption of the computer media in the pedagogical field, new ways of doing things in education have been consolidated where Heritage Education has an important ally. The increasingly widespread use of smartphones and other mobile devices among the educational community makes possible to apply novel strategies to improve the  learning process. This study is aimed to support the introduction of educational activities associated to the Mobile Learning and also to contributed to perfectionate  Heritage Education as a subject taught in the courses of  Bachelor Degree in Education, specialty Geography, of the Universidad Central   Marta Abreu de las Villas. The results of this research are based on the  analysis of following the categories: knowledge self-management, learning motivation,  informational skills development, student´s self-preparation  and  assessment transformations.
THE RELATIONSHIP BETWEEN TOLERANCE OF UNCERTAINTY AND PARAMETERS OF CREATIVITY OF STUDENTS

Uncertainty tolerance is a systematic, persistent tendency of a person to react more or less intensely to the perceived ambiguity. Tolerance of uncertainty is activated in situations of decision-making or solving problems. How productive can be people’s behavior in unexpected, uncertain situations is largely determined by their creative potential. In the circumstances of ambiguity and multitasking, uncertainty tolerance and creativity are included in the structure of essential qualities of various professional careers, which emphasizes the necessity to study the correlation between these phenomena. There are 148 students from Novosibirsk State Medical University – the 1st, 2nd, and 3rd-year students – taking part in the empirical study. Among them are 25 boys and 123 girls. The average age of the subjects is 20±2.2 years. The data obtained from the study demonstrate a significant positive correlation between uncertainty tolerance and many creativity indicators. This proves that students with a high level of uncertainty tolerance have a higher level of real (originality, emotional sensitivity/empathy) and ideal parameters of creativity (imagination, creative thinking, originality, curiosity). Thus, situations that generate ambiguity and uncertainty engage students’ creative potential and allow for unconventional decisions, flexible behavior, perception of various aspects of a problem, and emotional response to the ambiguity.
Pengenalan Coding Bagi Usia Sekolah Menggunakan Aplikasi SHINIBIK (Shinhan University dan IBI Kosgoro 1957) Bagi Murid Sekolah Dasar Negeri 11 Lenteng Agung Jakarta Selatan

Industrial Era 4.0 brought Indonesian people to a technological mindset that covered various aspects of life. Technology is now open again to luxury things (luxury) so that people can not be separated from the rise of technological facilities. In preparation for entering the industrial era 5.0, there is no doubt that information retrieval is greatly supported and facilitated by various technology-based devices and applications. Information which is currently an important basic material in shaping concrete data makes information important in various aspects of life.Based on the adage not know then do not love will bring every human being will continue to need information that is used to recognize something so that it can more quickly adapt and easily accept the positive things that exist. For this reason, the existence of a computer-based application created by using a specific programming language coding as a tool that can help humans in finding things that can be information for him. Responding to this matter, where there are still so many people who are not familiar with coding, especially in school-age children, we intend to help one of the current government programs, which is helping programs that lead people to better recognize coding, especially at school age.
An Error Analysis of English as a Foreign Language (EFL) Students’ Works on Simple Present Tense

Verb tenses in English has been challenging for the students even they have already been studying English for many years. The tense system in students’ first language may be very different from English that it takes some more time for the English as a Foreign Language (EFL) students to master it. This research, therefore, is carried out to analyze the errors that are commited by the students in learning simple present tense. This study presents qualitative research conducted through analysis of students’ answer sheet about changing the sentences into negative and interrogative in the form of present tense. Nineteen English Department students at the first year were taken as the subject of this research.  The data are checked one by one by applying error analysis (EA) to identify errors. From this investigation, it is found that there are 288 errors done by the students. These errors are subsequently analyzed and classified based on surface strategy taxonomy: omission, addition, misinformation, and misordering. The number of errors for each category is 68 (23,61%), 23 (7,99%), 143 (49,65%), and 54 (18,75%) respectively. It can be seen that the most frequent error emerged on the students’ works is misinformation, more than half of the total errors (49,65%), while the least common error committed is addition, not reaching a tenth of all  (7,99%). This finding provides an illustration of students’ weakness in learning simple present tense which can be beneficial either for students or for the lecturer in the future. It is suggested that the students be more focused on parts they are weak in when learning grammar to reach a better understanding. The lecturer also can provide a more appropriate teaching material or method highlighting the more demanding part by his or her students.
An Image Enhancement Method Based on MSR and HDRC for Underwater Images

An image enhancement method based on multi-scale Retinex (MSR) and high dynamic range compression(HDRC) is proposed to solve underwater image quality problem, such as low illumination and uneven illumination. Firstly, for the Halo Effect caused by MSR algorithm, a HDRC method is proposed to compress the RGB values of each channel in different degrees, which can not only suppress the Halo Effect, but also improve the color deviation effect caused by the underwater environment. Then, the low-frequency noise is filtered by Gauss high-pass filter to enhance image contrast and clarity. Finally, the chromaticity is restored by the color saturation adjustment function. Experiments are carried out onthree kinds of uneven illumination underwater images, and provethe competitive performance of the proposed method. Twotraditional underwater image evaluate metrics, underwater color image quality (UCIQE) and underwater image quality (UIQM) are selected to assess the proposed method. The experiments results showed that the proposed algorithm provides more details enhancement and more natural colorfulness restoration as compared to other existing image enhancement methods. The proposed algorithm can effectively reduceHalo Effect and noise, improve the image quality for uneven illumination underwater image.
Rancang Bangun Sistem Informasi Manajemen Laundry Pada Klin En Klin Laundry

Klin en Klin is a business that is engaged in clothes washing and ironing services that are starting to develop. Where this laundry business provides kilogram washing services and washing services that are calculated per item including washing and dry services and ironing services such as washing clothes, washing bad covers, washing blankets, washing curtains, washing dolls, washing bags, washing shoes, washing helmets, washing carpets, wash the coat. The management process in this laundry service activity is still manual. In data collection activities, customers' clothes are still very inefficient because data collection is still using paper and handwritten. When the customer comes to hand over the goods, the recording of goods data and making notes is still using paper so that when the data is stored or archived, the data is prone to loss or damage which could result in negligence or natural disaster. In addition, financial statements can also be miscalculated. Transaction systems that are still manual and still not optimal have found problems such as accumulation of records and reports, slow information flow, slow data retrieval process and difficult transaction report recap. To overcome this problem, a laundry management information system is needed that can increase the effectiveness and efficiency of the Klin En Klin Laundry business. The purpose of this research is to produce a web-based software application using the PHP programming language and MySQL database to design a Laundry Management System. The result of this design is to produce a Web-based application that can be a medium of information to help laundry service businesses in managing their management