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"In and out of formal schooling, online and off, today’s learners must consume and integrate a level of information that is exponentially larger and delivered through a wider range of formats and viewpoints than ever before. The Handbook of Learning from Multiple Representations and Perspectives provides a path for understanding the cognitive, motivational, and socioemotional processes and skills necessary for learners across educational contexts to make sense of and use information sourced from varying inputs. Uniting research and theory from education, psychology, literacy, library sciences, media and technology, and more, this forward-thinking volume explores the common concerns, shared challenges, and thematic patterns in our capacity to make meaning in an information-rich society.Chapter 16 of this book is freely available as a downloadable Open Access PDF under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license available at"

"The static properties of hadrons, such as their radii and other moments of the electric and magnetic distributions, canonly be extracted using theoretical methods and cannot be directly measured from experiments. As a result,discrepancies between the extracted values from different precision measurements can exist. The proton charge radius,rp, which is extracted either from electron-proton (e-p) elastic scattering data or from hydrogen atom spectroscopy,seems to be no exception. The value rp = 0.84087(39) fm extracted from muonic hydrogen spectroscopy is about 4%smaller than that obtained from e-p scattering or standard hydrogen spectroscopy. The resolution of this so-calledproton radius puzzle has been attempted in many different ways over the past six years. The present article reviewsthese attempts with a focus on the methods of extracting the radius.Ekstraksi Radius Muatan Proton dari Eksperimen. Sifat-sifat statik hadron seperti radius serta momen-momen laindari distribusi listrik dan magnetik hanya dapat diekstrak melalui metode teoretis dan tidak dapat langsung diukurmelalui eksperimen. Akibatnya, perbedaan antara nilai-nilai yang diekstrak dari pelbagai pengukuran berbeda seringterjadi. Radius muatan dari proton, rp, yang diekstrak dari data hamburan elastik elektron proton atau dari spektroskopiatom hidrogen merupakan salah satu contoh problem ini. Nilai rp = 0.84087(39) fm yang diekstrak dari spektroskopihidrogen muonik diketahui 4% lebih kecil dibandingkan dengan nilai yang diperoleh dari hamburan elastik elektronproton atau pun dari spektroskopi hidrogen baku. Pemecahan masalah yang sering disebut teka-teki radius proton inisudah banyak dicoba dengan menggunakan pelbagai cara selama enam tahun terakhir. Makalah ini mengulas usahausahatersebut dengan fokus metode ekstraksi radius."

"Peningkatan jumlah data teks digital membuat manusia membutuhkan mekanisme untuk mengembalikan teks yang efektif dan efisien. Salah satu mekanisme untuk mengembalikan teks adalah dengan pemeringkatan teks. Tujuan dari pemeringkatan teks adalah menghasilkan daftar teks yang terurut berdasarkan relevansinya dalam menanggapi permintaan kueri pengguna. Pada penelitian ini, penulis menggunakan Bidirectional Encoder Representations from Transformers (BERT) untuk membangun model pemeringkatan teks berbahasa Indonesia. Terdapat 2 cara penggunaan BERT untuk pemeringkatan teks, yaitu BERT untuk klasifikasi relevansi dan BERT untuk menghasilkan representasi vektor dari teks. Pada penelitian ini, 2 cara penggunaan BERT tersebut terbagi menjadi 4 model, yaitu BERTCAT, BERTDOT, BERTDOTHardnegs, BERTDOTKD. Penggunaan BERT memberikan peningkatan kualitas pemeringkatan teks bila dibandingkan dengan model baseline BM25. Peningkatan kualitas pemeringkatan teks tersebut dapat dilihat dari nilai metrik recriprocal rank (RR), recall (R), dan normalized discounted cumulative gain (nDCG).

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The increase in the amount of digital text data has led humans to require mechanisms for effectively and efficiently retrieving text. One mechanism for text retrieval is text ranking. The goal of text ranking is to generate a list of texts sorted based on their relevance in response to user query requests. In this study, the author uses Bidirectional Encoder Representations from Transformers (BERT) to build a text ranking model for the Indonesian language. There are 2 ways to use BERT for text ranking, namely BERT for relevance classification and BERT for generating vector representations of text. In this study, these 2 ways of using BERT are divided into 4 models, namely BERTCAT, BERTDOT, BERTDOTHardnegs, BERTDOTKD. The use of BERT improves the quality of text ranking compared to the baseline BM25 model. The improvement in the quality of text ranking can be seen from the values of the reciprocal rank (RR), recall (R), and normalized discounted cumulative gain (nDCG) metrics."

"This book elucidates the importance of long-term experiments in revealing evidence of soil fertility decline in Africa. An evaluation of experiences from on-going long-term experiments is given in broad detail. The first chapter explains the paradigm shift in soil fertility management then provides justification for long-term experiments before illuminating experiences from long-term experiments in East, West and Southern Africa. The second, sixth, eighth and ninth chapters give an in-depth account of crop management practices and soil fertility interventions in long-term trials within specific agro-ecological zones in West Africa. The rest of the chapters (chapter three, four, five and seven) address crop management, tillage practices and, organic and inorganic fertilizer applications in the context of long-term experiments in specific agro-ecological zones in East Africa."

"This article introduces two interconnected approaches to provenance research on anthropological facial plaster-casts taken from living individuals. It focuses on three series of facial casts taken by Dutch anthropologist Johannes Pieter Kleiweg de Zwaan (1875-1971) in the Netherlands East Indies in 1907 and 1910. It suggests that “reading” the facial casts as an archive of faces and an archive of plaster has the potential to reveal information systematically left out in their object biographies. Through this reading process, the colonial networks of control and power asymmetries which made the plaster-casting possible are examined. It seeks out additional information to bring the object closer to the person whose face was appropriated for various colonial ends. This epistemological experiment explores the first steps which can be taken to create a decolonial view of the large anthropological plaster-cast collections in European museums which have been left anonymous for decades."

"Peraturan perundang-undangan baru di Indonesia dapat mengganti, menghapus, atau menambahkan aturan yang sudah berlaku sehingga setiap warga Indonesia memiliki tanggung jawab untuk mengetahui aturan terbaru saat hendak digunakan. Laman pengumpulan informasi ini sudah ada di laman pemerintah resmi seperti peraturan.go.id. Akan tetapi ada informasi yang tidak mudah dicari seperti isi pasal terbaru pada doku- men yang telah diubah oleh dokumen lain. Sekarang, sudah ada informasi peraturan perundang-undangan yang disimpan dalam knowledge graph (KG)-sebuah basis data terstruktur berbentuk kumpulan entitas dan relasi layaknya sebuah graf- bernama LexID KG (Muninggar & Krisnadhi, 2023). Ditambah lagi, LexID QA (Handi, 2023), yaitu sebuah sistem tanya jawab hukum dengan informasinya dari LexID KG, menangani masalah ini tetapi dengan memaksakan struktur inputnya. Menurut Jain, Kumar, Kota, dan Patel (2018) kebebasan membuat input (free-text) merupakan tur bagus karena seakan-akan sedang berinteraksi dengan manusia. Oleh karena itu, penelitian ini berusaha untuk menyelesaikan permasalahan pemaksaan struktur input pada LexID QA dengan beralih ke model machine learning pipeline. Model pipeline-nya tersusun dari model klasi kasi pertanyaan bebas ke kueri SPARQL, sebuah bahasa untuk mengambil informasi dari KG, dan model NER untuk mengambil informasi entitas penting seperti judul dokumen yang dicari pada pertanyaan bebasnya. Kedua model ini berbasiskan BERT (Bidirectional Encoder Representations from Transformers) (Devlin, Chang, Lee, & Toutanova, 2018). Hasil dari model klasi kasi mencapai nilai sempurna pada dataset baru yang dibuat pada penelitian ini. Kemudian, hasil dari model pipeline-nya juga mencapai nilai makro-akurasi sebesar 0.949 pada dataset yang sama.

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New laws and regulations in Indonesia can modify, repeal, or adding to existing rules so that every Indonesian citizen has responsibility to know the latest rules when utilizing them. This collection of information is available on of cial government websites such as peraturan.go.id. However, there is information that not easy to nd, such as the contents of latest articles in the documents that have been modi ed by another document. Currently, there is regulatory information stored in a knowledge graph (KG)-a database structured in the form of a collection of entities and relationships like a graph- called LexID KG (Muninggar & Krisnadhi, 2023). Additionally, LexID QA (Handi, 2023), a legal question and answer system with information from LexID KG, addresses this problem but forcing its input structure. According to Jain et al. (2018), free-text input is a good feature because it feels like communication with humans. Therefore, this research trying to solve the problem of forcing input structures in LexID QA by transitioning to a machine learning pipeline model. The pipeline model is composed of free question classi cation model to query SPARQL, a language for retrieving information from KG, and NER model to extracting important entity such as legal title in the free-text input. Both model are based on BERT (Bidirectional Encoder Representations from Transformers) (Devlin et al., 2018). The classi cation model achieved a perfect score on the new dataset created in this research. Furthermore, the pipeline model achieved a macro-accuracy score of 0.949 on the same dataset."