bluuebunny/crossref_metadata_2025 huggingface dataset:
SİVAS İLİNDE TELKÂRİ İŞLEMECİLİĞİ VE SON TEMSİLCİLERİNDEN NİYAZİ ARSLANHAN’IN ÇALIŞMALARI
Authors: SAKLAVCI Fatmagül
Published: September 2023

Anadolu'daki çeşitli medeniyetlere ait gümüş işçiliği ile hazırlanan eşyalar, gümüş işçiliğinin tarihinin milattan öncelere kadar gittiğini göstermekte, o dönem insanlarının kültürlerini, sosyo-ekonomik durumlarını, yaşam tarzlarını, zevklerini ve kültürlerarası etkileşimlerini ortaya koymaktadır. Türk gümüş işçiliği Orta Asya'da yayılmaya başlamış, Anadolu'da İslamiyet ile birlikte altın ve gümüş kullanımı artmış, Anadolu Selçuklu ve Osmanlı dönemlerinde önemini korumuştur. Osmanlıların Balkan toprakları üzerindeki hâkimiyetini kaybetmesinden sonra burada yaşayan halk Sivas gibi Anadolu'nun çeşitli yerlerine yerleşerek kültür ve sanatlarını da beraberinde getirmişlerdir. Bu bölgelere yerleşen göçmenler arasında Sivas gümüş ustalarının bir kısmının atalarının da zanaatkâr olduğu bilinmektedir. 1950'li ve 1960'lı yıllarda Sivas'ta gümüş ustalarının sayısı yüzden fazla iken, birçoğu İstanbul'a veya yurt dışına giderek mesleği bırakmıştır. Günümüzde Sivas ilinde kaybolmaya yüz tutmuş mesleklerden biri olan gümüşçülükle uğraşan birkaç usta bulunmaktadır. Telkâri için kullandığı gümüş malzeme İstanbul Kapalıçarşı'dan getirtilen gümüşü ocaklarda eriterek tele dönüştürülmektedir. Tarak, kerpeten, ikili, kancalı, zarlı hendek takımları gibi geleneksel malzemeler kullanılarak vav, sim, damla, mekik dolgu teknikleri ile formlar oluşturulmaktadır. Formların oluşturulmasında tarak, kerpeten, çifte, çengel, zar heşdek takımı gibi geleneksel malzemeler kullanılmaktadır. Boraks, lehim ve teneker yardımıyla son şekli verilen kolye, yüzük, bileklik, kalem, kutu gibi parçalar top ve iğne dolabında temizlenir ve parlatılır. Geleneksel yöntemlerle yapılması oldukça zahmetli olan telkâri sanatı teknolojiye yenik düşer, ürün çeşitliliği artar ancak maliyetlerden dolayı talep azalır. Bu çalışmayı yapmaktaki amacımız Sivas’ta nalbantlık, bıçakçılık ve çubukçuluk gibi zamana ve şartlara yenik düşen sanat ve mesleklerin tarihçesini ve bugünkü durumunu araştırmak ve ustalarını tanıtarak gelecek nesillere aktarmaktır.
Athenian Logomachy in The Human Stain and Philip Roth’s Fight for the Word
Authors: Gustafson Thomas
Published: September 2023

Abstract: In The Human Stain (2000), Philip Roth develops a concern that animates his canon: the potentials and dangers of our most human trait—our capacity to fire back and forth words and letters. For Coleman Silk, in the world of Athena College—just as in ancient Athens—the battle of words in the forum becomes as dangerous as the battle of swords on the Homeric battlefield, and a mission of Roth in this novel, as in other works, is to turn logomachy into self-reflective art about the violence and corruption of the word in the American city-state.
When She Was Good and the Eclipse of the Virtuous Heroine: A Revaluation
Authors: Brown Julia Prewitt
Published: September 2023

Abstract: Beginning with a brief discussion of the lack of serious revaluations of Roth’s work amidst the scandal surrounding Roth’s biographer Blake Bailey, this essay considers the overlooked importance of Roth’s early satiric novel, When She Was Good (1967). The novel may be said to mark Roth’s lasting challenge to the Anglo-American tradition of the heroine distinguished above all by her virtuous character. Roth implicitly alludes to earlier saintly heroines in his portrait of Lucy Nelson, who, as she comes of age, ultimately embodies the apotheosis of what Harold Bloom has called “the heroine of the Protestant will.” Roth’s representation of the American middle class Protestant value system, with its imperial conviction of its own righteousness and its blind sentimentalization of the women who carried its banner, freed Roth to write his next novel, Portnoy’s Complaint (1969). It was as if exorcising the demonically virtuous shiksa Lucy Nelson was necessary before he could speak in his own voice. In When She Was Good , Roth explores a psychology of personal grievance that resonates eerily on both sides of the political spectrum today.
Networks analysis of Brazilian climate data based on the DCCA cross-correlation coefficient
Authors: Oliveira Filho Florêncio Mendes , Guedes Everaldo Freitas , Rodrigues Paulo Canas
Published: September 2023

Climate change is one of the most relevant challenges that the world has to deal with. Studies that aim to understand the behavior of environmental and atmospheric variables and the way they relate to each other can provide helpful insights into how the climate is changing. However, such studies are complex and rarely found in the literature, especially in dealing with data from the Brazilian territory. In this paper, we analyze four environmental and atmospheric variables, namely, wind speed, radiation, temperature, and humidity, measured in 27 Weather Stations (the capital of each of the 26 Brazilian states plus the federal district). We use the detrended fluctuation analysis to evaluate the statistical self-affinity of the time series, as well as the cross-correlation coefficient ρDCCA to quantify the long-range cross-correlation between stations, and a network analysis that considers the top 10% ρDCCA values to represent the cross-correlations between stations better. The methodology used in this paper represents a step forward in the field of hybrid methodologies, combining time series and network analysis that can be applied to other regions, other environmental variables, and also to other fields of research. The application results are of great importance to better understand the behavior of environmental and atmospheric variables in the Brazilian territory and to provide helpful insights about climate change and renewable energy production.
Qualitative analysis of the coding of pathological data of cancer registry centers: A study in North of Iran
Authors: Jahani Mohammad-Ali , Mahmoudi Ghahraman , Nikbakht Hossein-Ali , Farhadi Zeinab , Mousavi Raziehsadat
Published: September 2023

Background

The cancer registry system is an important part of the cancer control program. Improper coding of cancers leads to misclassification and incorrect statistical information about cancer. Therefore, in this study, the main objective of the qualitative analysis was the accuracy in assigning the codes to the pathological reports in the centers responsible for cancer registry.

Methods

This study was descriptive, retrospective and applied. The data source in this study included 15,659 pathology reports received during the years 2017–2019 in the population-based cancer registry centers of Mazandaran province. Out of 1800 reports, 1765 samples of reports were selected and analysis was done on them by stratified random sampling method. A researcher-made checklist was used to collect data, and the Kappa agreement coefficient and Cohen’s agreement percentage were presented to check the accuracy of the reports. STATA13 was used for data analysis.

Results

1150 of 1765 pathology reports (65.0%), did not have a topographic, morphological and behavioral codes and 410 (23.2%) had grade codes. The Kappa coefficient in reports with a topography code was 0.916 and with a morphology code it was 0.929, respectively. In behavior coding, the highest agreement is in the category of benign cancers at 65.2% and in grade coding in the category without grade is 100%.

Conclusion

The most reports were on carcinoma morphology, and the Kappa coefficient in morphology codes has almost complete reliability. In terms of behavior coding, there was the most agreement in the category of benign cancers. The Kappa coefficient in given behavior codes has low reliability.
Socioeconomic status and subjective well-being: The mediating role of class identity and social activities
Authors: Wang Baoqin , Zhao Hang , Shen Hao , Jiang Yi
Published: September 2023

Background

Subjective well-being has a significant impact on an individual’s physical and mental health. Socioeconomic status, class identity, and social activity participation play important roles in subjective well-being. Therefore, the aim of this study was to uncover the mechanisms through which these factors influence subjective well-being.

Methods

A total of 1926 valid samples were recruited using the Chinese General Social Survey 2021 (CGSS 2021). The Chinese Citizen’s Subjective Well-Being Scale (SWBS-CC) was employed to assess subjective well-being. Socioeconomic status was measured using income and education, and class identity and social activity participation were measured using Likert scales. Pearson correlation analysis and the chain mediation model were conducted to explore the relationship between these factors. Finally, the Bootstrap method was used to examine the path coefficients.

Results

A significant correlation was found between socioeconomic status, class identity, social activity, and subjective well-being (p < 0.01). The indirect effect of socioeconomic status on subjective well-being mediated by class identity was 0.351 (95% CI: 0.721, 1.587), while the indirect effect of socioeconomic status on subjective well-being mediated by social activity was 0.380 (95% CI: 0.059, 0.240). The effect mediated by both class status and social activities was 0.011 (95% CI: 0.010, 0.093).

Conclusions

The study showed that socioeconomic status, class identity, and social activity had significant effects on subjective well-being. Class identity and social activity partially mediated the effects of socioeconomic status on subjective well-being, and they had a chain mediating effect between socioeconomic status and subjective well-being. Therefore, policymakers have the opportunity to enhance subjective well-being in lower socioeconomic status groups by promoting individual class identity and encouraging greater social activity participation.
Geospatial availability of breast cancer treatment modalities and hypothetical access improvement in Ghana: A nationwide survey
Authors: Schoenhals Sarah , Mali Meghan E. , Sutherland Edward K. , Sorenson Justin , Dedey Florence , Nellermoe Jonathan , Flores-Huidobro Martinez Angel , Tounkara Mamadou D. , Price Raymond R. , Brownson Kirstyn E.
Published: September 2023

Breast cancer in Ghana is a growing public health problem with increasing incidence and poor outcomes. Lack of access to comprehensive treatment in Ghana may be a contributing factor to its high mortality. The purpose of this study was to evaluate the availability of treatments nationwide and systematically identify high yield areas for targeted expansion. We conducted a cross-sectional, nationwide hospital-based survey from November 2020-October 2021. Surveys were conducted in person with trained research assistants and described hospital availability of all breast cancer treatments and personnel. All individual treatment services were reported, and hospitals were further stratified into levels of multi-modal treatment modeled after the National Comprehensive Cancer Network (NCCN) Framework treatment recommendations for low-resource settings. Level 3 included Tamoxifen and surgery (mastectomy with axillary lymph node sampling); Level 2 included Level 3 plus radiation, aromatase inhibitors, lumpectomy, and sentinel lymph node biopsy; Level 1 included Level 2 plus Her2 therapy and breast reconstruction. Hospitals were identified that could expand to these service levels based on existing services, location and personnel. The distance of the total population from treatment services before and after hypothetical expansion was determined with a geospatial analysis. Of the 328 participating hospitals (95% response rate), 9 hospitals had Level 3 care, 0 had Level 2, and 2 had Level 1. Twelve hospitals could expand to Level 3, 1 could expand to Level 2, and 1 could expand to Level 1. With expansion, the population percentage within 75km of Level 1, 2 and 3 care would increase from 42% to 50%, 0 to 6% and 44% to 67%, respectively. Multi-modal breast cancer treatment is available in Ghana, but it is not accessible to most of the population. Leveraging the knowledge of current resources and population proximity provides an opportunity to identify high-yield areas for targeted expansion.
Latitude and longitude as drivers of COVID-19 waves’ behavior in Europe: A time-space perspective of the pandemic
Authors: Martínez-Portillo Alejandro , Garcia-Garcia David , Leon Inmaculada , Ramis-Prieto Rebeca , Gómez-Barroso Diana
Published: September 2023

Background

Social restrictions and vaccination seem to have shaped the pandemic development in Europe, but the influence of geographical position is still debated. This study aims to verify whether the pandemic spread through Europe following a particular direction, during the period between the start of the pandemic and November 2021. The existence of a spatial gradient for epidemic intensity is also hypothesized.

Methods

Daily COVID-19 epidemiological data were extracted from Our World in Data COVID-19 database, which also included vaccination and non-pharmacological interventions data. Latitude and longitude of each country’s centroid were used as geographic variables. Epidemic periods were delimited from epidemic surge data. Multivariable linear and Cox’s regression models were performed for each epidemic period to test if geographical variables influenced surge dates. Generalized additive models (GAM) were used to test the spatial gradient hypothesis with three epidemic intensity measures.

Results

Linear models suggest a possible west-east shift in the first epidemic period and features a significant association of NPIs with epidemic surge delay. Neither latitude nor longitude had significant associations with epidemic surge timing in both second and third periods. Latitude displays strong negative associations with all epidemic intensity measures in GAM models. Vaccination was also negatively associated with intensity.

Conclusions

A longitudinal spread of the pandemic in Europe seems plausible, particularly concerning the first wave. However, a recurrent trend was not observed. Southern Europe countries may have experienced increased transmissibility and incidence, despite climatic conditions apparently unfavourable to the virus.
livro e as políticas públicas
Authors: Pereira de Almeida Laura , Corrêa Pires Dornelles Beatriz
Published: September 2023

O presente trabalho busca compreender de que forma a implementação de políticas públicas no Brasil é capaz de influenciar o hábito de leitura. Temos como objetivo observar a história das políticas públicas que envolvem o livro em busca de compreender os índices de leitura atuais do país, publicados na pesquisa “Retratos da Leitura no Brasil”. Essa é uma pesquisa exploratória, bibliográfica e documental e com método indutivo. Observamos que, a partir da época do Brasil Colônia, houve um atraso até o Estado começar a aplicar políticas públicas efetivas de incentivo à leitura de livros. Através desse artigo, conseguimos visualizar a importância e a necessidade de manter políticas públicas efetivas em torno do livro e da leitura. Para um maior acesso aos livros e à leitura no país, é necessário investimento do Estado.
Encontro do sentido de vida pelo trabalho criativo: a percepção de ex-voluntários do Projeto Terapeutas da Alegria da Univali através da Clownterapia
Authors: Generoso Nhayara , Dittrich Larissa Fernanda
Published: September 2023

Esta pesquisa teve como objetivo geral identificar a percepção de ex-voluntários que realizaram intervenções com seu clown no projeto “Terapeutas da Alegria” da Univali, para o encontro do sentido de vida através do trabalho criativo da clownterapia. O clown tem origem circense, e utiliza o lúdico e o improviso, o que caracteriza um trabalho criativo. No hospital, o clown, possui um papel de humanização da saúde, podendo levar pacientes a entrarem em contato com as suas emoções, como a alegria expressada pelo riso, através do que é conhecido como terapia do riso ou clownterapia, que possui benefícios na melhora do quadro biológico e psicológico. A elaboração desta atividade foi realizada por voluntários, portanto, um trabalho não remunerado. Esta pesquisa, de abordagem qualitativa e de cunho teórico e prático teve fundamentos no campo teórico da logoterapia de Frankl, que afirma que o sentido da vida pode ser encontrado por três caminhos: do amor, sofrimento e do trabalho criativo. Como resultado, identificamos o encontro de sentido de vida para ex-voluntários do projeto, uma vez que foi evidenciada esta vivência de sentido, e portanto, confirmou o encontro do sentido de vida através do trabalho criativo da clownterapia.
Estudios Artísticos: una revista y un doctorado en un mismo horizonte decolonial
Authors: Gómez Moreno Pedro Pablo
Published: September 2023

Estudios Artísticos además de ser la denominación de una revista académica es un programa de formación de nivel doctoral de la Facultad de Artes, ASAB, de la Universidad Distrital Francisco José de Caldas. En este breve texto de apertura al número 15 de la revista se pondrá el acento en los Estudios Artísticos como programa de formación de nivel doctoral.
Intertextualidad excéntrica, arte y violencia: connivencia y altertopía en las camas de la muerte del arte objetual colombiano
Authors: Pineda Repizo Adryan Fabrizio
Published: September 2023

Este texto, resultado del proyecto doctoral Extrañamientos del objeto del uso en el arte de Colombia, da continuación a la investigación en torno al planteamiento de la noción de intertextualidad excéntrica a partir de las correlaciones que emergen del encuentro poético entre la red de significación del objeto de uso y la intervención artística. Este encuentro, denominado arte objetual, pone en correlación elementos que ilustran la manera en que se constituye el sentir y lo común en la cultura colombiana. Pero a la vez también expresan la demanda de rearticulación de lo crítico y lo opresivo que desde el arte se plantea. Al considerar la tensión entre estas dos tendencias, se revela que la intertextualidad se cruza con las relaciones de poder en el orden interdiscursivo y que, desde allí, adquiere una función crítica y creativa. El texto propone interpretar esta tensión en términos de las categorías de connivencia y altertopía y para establecerlas recurre al diálogo con algunas obras de arte objetual enfocadas en la temática de la experiencia de la violencia en Colombia
Carnaval de Montevideo (Uruguay) Una fugaz mirada a varios de sus actos festivos (febrero 17 a 22 de 2023)
Authors: González Pérez Marcos
Published: September 2023

El Carnaval de Montevideo (Uruguay) tiene como característica esencial el ser un carnaval teatralizado. Las puestas en escena de lo carnavalesco a través de los grupos artísticos que conforman las murgas, revistas, comparsas, humoristas y parodistas muestran con espectacularidad la teatralidad, los vestuarios, las músicas y las dramaturgias que los creadores, artistas, artesanos y personal de apoyo logran ambientar en los escenarios. Las murgas están plenas de músicas, letras, danzas y cantos cuyo eje es la sátira social o política de acontecimientos o personajes de la vida (uruguaya). Es en este tipo de muestra cultural donde la risa construye escenarios de lo fantástico y crea una ruptura fuerte con lo cotidiano. La comparsa es África en América con sus músicas de candombe, sus danzas, sus toques de tambores y su relación con lo afrouruguayo; son comparsas de negros y de lubolos acompañados con las danzas de mujeres que construyen un universo de lo bello. Este tipo de elementos, propios del evento, se muestra en este relato de imágenes que dan cuenta de la espectacularidad de un carnaval considerado por su duración de 45 días el más largo del mundo, pero también visto como único en la creación de escenografías donde los elementos de lo festivo dejan ver la cultura del pueblo uruguayo.
Sketch de una taxidermia a Colombianización de Nadia Granados
Authors: Fajardo Leal Laura Paola
Published: September 2023

En un intento por desarrollar una intrépida taxidermia discursiva, este artículo recorre el proyecto ganador de la XI versión del Premio Luis Caballero (2022): Colombianización de la artista Nadia Granados. Así pues, a la luz del concepto de “gramática cultural” se indaga de qué manera las prácticas hegemónicas y coloniales en nuestro país legitiman una suerte de identidad nacional anclada a estructuras biopolíticas que contribuyen al disciplinamiento del ser, sentir y pensar, las cuales reafirman una representación colectiva orientada a asumirnos como “el país más feliz del mundo”. En consecuencia, se revisa a detalle cuáles son las implicaciones culturales y sociopolíticas de una marca país y de la legitimación de la barbarie que, como vehículos ideológicos, contribuyen a la difusión mediática de producciones significan[1]tes en una sociedad del consumo y la tanatofilia; difusión que suscita una predilección hacia la violencia, el individualismo y anula toda idea de otredad-humanidad.
Recent Findings in Malaria Emergence of Piperaquine-Resistant Plasmodium falciparum Genes in Malaria Endemic Areas of Indonesia: a Literature Review
Authors: Sari Ayu Nurdiantika , Wahyono Tri Yunis Miko , Kosasih Ayleen Alicia , Samosir Yoshida Aussiana , Taufiq Rania Rifdah , Sutanto Inge
Published: September 2023

Background: In recent years, artemisinin and piperaquine (PPQ) resistance in the Greater Mekong Sub-region alarmed Southeast Asian countries, especially those relying on artemisinin- based combinations as antimalarial drugs. This study aims to review the current status of malaria research and examine the frequencies of piperaquine resistance in Plasmodium falciparum isolates originating from malaria-endemic areas in Indonesia.Methods: We undertook a review to identify empirical data on antimalarial piperaquine-inclusive artemisinin combination therapies (ACT) in Indonesia using studies conducted since 2015. Journal articles were searched using the keywords combination of malaria, piperaquine, Pfcrt, Pfmdr, Pfpm2, and Indonesia. The search was conducted in four databases. Trends in empirical data were summarised in a table and compared with emerging malaria prevalence and conditions in Indonesia.Results: Our study found that dihydroartemisinin-piperaquine (DHA-PPQ) is still effective in most area. Survey of PPQ resistance in regions using DHA-PPQ as the first-line treatment heavily depends on phenotypic tests of the given drug resistance. Molecular surveys exploring polymorphisms of Pfcrt, Pfmdr1, and Pfpm2 were not found.Conclusion: This study supports the use of dihydroartemisinin-piperaquine as the first-line antimalarial drug in malaria endemic areas of Indonesia. Further research examining efficacy is required to monitor piperaquine resistance in Indonesia.
Penurunan Nilai pH pada Bakteri Lactobacillus bulgaricus di dalam Media yang Mengandung D-tagatosa dan D-fruktosa
Authors: Sari Dewi Indah , Legowo Anang Mohammad , Al-Baarri Ahmad Ni'matullah
Published: September 2023

Penelitian ini bertujuan untuk menganalisis nilai pH pada pertumbuhan Lactobacillus bulgaricus pada medium yang mengandung 3% (b/v) D-tagatosa dan D-fruktosa. Inkubasi dilakukan pada suhu 37˚C dan diukur selama 48 jam. Medium MRS broth juga digunakan sebagai pembanding. Berdasarkan penelitian ini dapat diketahui bahwa penurunan pH pada medium D-tagatosa dan D-fruktosa sebesar 18-20% sedangkan penurunan sebesar 31% terjadi pada media MRS broth. Penelitian ini dapat bermanfaat untuk memberikan informasi mengenai potensi D-tagatosa dan D-fruktosa sebagai medium yang dapat mempertahankan penurunan pH.This study aims to analyze the pH value on Lactobacillus bulgaricus medium containing 3% (w/v) D-tagatose and D-fructose. The incubation was conducted at 37°C. Changes in pH values were measured for 48 hours. The MRS broth medium was also used as a comparison. Based on this research it can be seen that D-tagatose and D-fructose medium decreased pH at a range 18-20% while MRS broth decreased 31%. This research might be useful to provide information on the potential of D-tagatose and D-fructose as a medium to maintain the reduction in pH.
Analisis Kadar dan Mutu Ecoenzim Kulit Nanas Dalam Pengawetan Buah Anggur dan Buah Tomat
Authors: Pravitasari Nadya , Astuti Andari , Maharani Endang
Published: September 2023

Buah tomat dan Buah annggur setelah pemanenan masih melakukan proses metabolisme sehingga berpotensi mengalami kerusakan. Buah  yang dipanen setelah timbul warna  10% sampai dengan 20% hanya tahan disimpan maksimal selama 7 hari pada suhu kamar. Penelitian ini bertujuan untuk mengetahui pengaruh ecoenzim dalam proses pengawetan buah anggur dan buah tomat. Bahan yang digunakan dalam  penelitian ini adalah kulit buah nanas kering, setengah kering dan basah.. Penelitian menggunakan uji eksperimen acak lengkap dengan variasi perlakuan yang diberikan adalah tanpa diberi ekoenzim, perbandingan ekoenzim 6:4 , perbandingan 4;6, dan ekoenzim murni. Parameter yang diamati adalah kadar air, suhu, mutu buah. Data aktivitas uji ekoenzim kulit nanas pada buah anggur dan buah tomat ceri dianalisis secara kuantitatif. Data hasil pegujian ekoenzim dapat menjadi alternatif pengganti pelapisan lilin ataupun agar-agar. Dalam penyimpanan dala pengawetan juga dipengaruhi oleh suhu semakin rendah bakteri yang ada dalam buah akan melambat dan dapat mengurangi proses pembusukan. Kandungan dalam ekoenzim sangan aman karena terbuat dari kulit buah dan mengalami proses fermentasi yang menghasilkan mikroba hidup yang baik bagi tubuh.
Pemanfaatan Limbah Onggok Aren dan Ampas Tebu sebagai Inovasi Batako Ramah Lingkungan
Authors: Antika Aisyah Rindi , Ashara Hilda Ari , Setiabudi Bambang , H Hartono
Published: September 2023

Batako merupakan bahan bangunan dinding yang saat ini banyak dipilih karena dinilai lebih efisien dalam segi pemasangan. Penelitian ini memanfaatkan limbah padat berupa onggok aren dan ampas tebu sebagai inovasi batako ramah lingkungan. Metode yang digunakan dalam penelitian ini adalah metode eksperimen. Parameter yang ingin dicapai dalam penelitian ini adalah nilai kuat tekan dan daya serap air yang diatur dalam SNI 03-0349-1989. Persentase abu ampas tebu yang akan ditambahkan adalah 0%, 2,5%, 5%, 7,5% dan 10% dari berat semen dan onggok aren sebesar 1% dari berat pasir dengan menggunakan FAS (Faktor Air Semen) sebesar 0,35. Nilai kuat tekan rata-rata dan penyerapan air yang dihasilkan adalah 10,52 Mpa dan 5,4%, 15,76 Mpa dan 4,9%, 17,62 Mpa dan 4,6%, 23,65 Mpa dan 4,5%, dan 5,14 Mpa dan 7,9%. Penggunaan kedua material ini dapat meningkatkan kuat tekan batako secara optimal pada persentase abu ampas tebu 7,5% dan onggok aren 1%. Inovasi ini dapat mengurangi limbah dan menjadi peluang bisnis batako bagi masyarakat setempat dengan biaya lebih rendah.
AutoSteer: Learned Query Optimization for Any SQL Database
Authors: Anneser Christoph , Tatbul Nesime , Cohen David , Xu Zhenggang , Pandian Prithviraj , Laptev Nikolay , Marcus Ryan
Published: September 2023

This paper presents AutoSteer, a learning-based solution that automatically drives query optimization in any SQL database that exposes tunable optimizer knobs. AutoSteer builds on the Bandit optimizer (Bao) and extends it with new capabilities (e.g., automated hint-set discovery) to minimize integration effort and facilitate usability in both monolithic and disaggregated SQL systems. We successfully applied AutoSteer on PostgreSQL, PrestoDB, Spark-SQL, MySQL, and DuckDB - five popular open-source database engines with diverse query optimizers. We then conducted a detailed experimental evaluation with public benchmarks (JOB, Stackoverflow, TPC-DS) and a production workload from Meta's PrestoDB deployments. Our evaluation shows that AutoSteer can not only outperform these engines' native query optimizers (e.g., up to 40% improvements for PrestoDB) but can also match the performance of Bao-for-PostgreSQL with reduced human supervision and increased adaptivity, as it replaces Bao's static, expert-picked hint-sets with those that are automatically discovered. We also provide an open-source implementation of AutoSteer together with a visual tool for interactive use by query optimization experts.
EmbedX: A Versatile, Efficient and Scalable Platform to Embed Both Graphs and High-Dimensional Sparse Data
Authors: Zou Yuanhang , Ding Zhihao , Shi Jieming , Guo Shuting , Su Chunchen , Zhang Yafei
Published: September 2023

In modern online services, it is of growing importance to process web-scale
graph data
and
high-dimensional sparse data
together into embeddings for downstream tasks, such as recommendation, advertisement, prediction, and classification. There exist learning methods and systems for either high-dimensional sparse data or graphs, but not both.

There is an urgent need in industry to have a system to efficiently process both types of data for higher business value, which however, is challenging. The data in Tencent contains billions of samples with sparse features in very high dimensions, and graphs are also with billions of nodes and edges. Moreover, learning models often perform expensive operations with high computational costs. It is difficult to store, manage, and retrieve massive sparse data and graph data together, since they exhibit different characteristics.

We present EmbedX, an industrial distributed learning framework from Tencent, which is versatile and efficient to support embedding on both graphs and high-dimensional sparse data. EmbedX consists of distributed server layers for graph and sparse data management, and optimized parameter and graph operators, to efficiently support 4 categories of methods, including deep learning models on high-dimensional sparse data, network embedding methods, graph neural networks, and in-house developed joint learning models on both types of data. Extensive experiments on massive Tencent data and public data demonstrate the superiority of EmbedX. For instance, on a Tencent dataset with 1.3 billion nodes, 35 billion edges, and 2.8 billion samples with sparse features in 1.6 billion dimension, EmbedX performs an order of magnitude faster for training and our joint models achieve superior effectiveness. EmbedX is deployed in Tencent. A/B test on real use cases further validates the power of EmbedX. EmbedX is implemented in C++ and open-sourced at https://github.com/Tencent/embedx.
SimpleTS: An Efficient and Universal Model Selection Framework for Time Series Forecasting
Authors: Yao Yuanyuan , Li Dimeng , Jie Hailiang , Jie Hailiang , Li Tianyi , Chen Jie , Wang Jiaqi , Li Feifei , Gao Yunjun
Published: September 2023

Time series forecasting, that predicts events through a sequence of time, has received increasing attention in past decades. The diverse range of time series forecasting models presents a challenge for selecting the most suitable model for a given dataset. As such, the Alibaba Cloud database monitoring system must address the issue of selecting an optimal forecasting model for a single time series data. While several model selection frameworks, including AutoAI-TS, have been developed to predict a dataset, their effectiveness may be limited as they may not adapt well to all types of time series, resulting in reduced prediction accuracy. Alternatively, models such as AutoForecast, which train on individual data points, may offer better adaptability but are limited by longer training time required.

In this paper, we introduce SimpleTS, a versatile framework for time series forecasting that exhibits high efficiency and accuracy across all types of time series data. When performing an online prediction task, SimpleTS first classifies input time series into one type, and then efficiently selects the most suitable prediction model for this type. To optimize performance, SimpleTS (i) clusters models with similar performance to improve the efficiency of classification; (ii) uses soft labeling and weighted representation learning to achieve higher classification accuracy for different time series types. Extensive experiments on 3 private datasets and 52 public datasets show that SimpleTS outperforms the state-of-the-art toolkits in terms of both training time and prediction accuracy.
PolarDB-SCC: A Cloud-Native Database Ensuring Low Latency for Strongly Consistent Reads
Authors: Yang Xinjun , Zhang Yingqiang , Chen Hao , Sun Chuan , Li Feifei , Zhou Wenchao
Published: September 2023

A classic design of cloud-native databases adopts an architecture that consists of one read/write (RW) node and one or more read-only (RO) nodes. In such a design, the propagation of write-ahead logs (WALs) from the RW node to the RO node(s) is typically performed asynchronously. Consequently, system designers either have to accept a loose consistency guarantee, where a read from the RO node may return stale data, or tolerate significant performance degradation in terms of read latency, as it then needs to wait for the log to be propagated and applied. Most commercial cloud-native databases, such as Amazon Aurora, choose performance over strong consistency. As a result, it makes RO nodes useless for many applications requiring read-after-write consistency (a form of strong consistency), and the support for serverless databases (i.e., allowing the RO nodes to be scaled out automatically) is impossible as they require a single endpoint.

This paper proposes
PolarDB-SCC
(PolarDB-Strongly Consistent Cluster), a cloud-native database architecture that guarantees strongly consistent reads with very low latency. The core idea is to eliminate unnecessary waits and reduce the necessary wait time on RO nodes while still supporting strong consistency. To achieve this, it tracks the RW node's modification timestamp at three progressively finer-grained levels. We further design a Linear Lamport timestamp to reduce the RO node's timestamp fetching operations and leverage the RDMA network for all the data transferring (
e.g.
, timestamp fetching and log shipment) to minimize network overhead and extra CPU usage. Our evaluation shows that PolarDB-SCC does not incur any noticeable overhead for ensuring strongly consistent reads compared with the eventually consistent (stale) read policy. To the best of our knowledge, PolarDB-SCC is the first "read-write splitting" cloud-native database that supports strongly consistent read with negligible overhead. Compared with a straightforward read-wait design, PolarDB-SCC improves throughput by up to 4.51× and reduces median latency by up to 3.66× in SysBench's read-write workload. PolarDB-SCC is already commercially available at Alibaba Cloud.
Machine Learning for Subgraph Extraction: Methods, Applications and Challenges
Authors: Yow Kai Siong , Liao Ningyi , Luo Siqiang , Cheng Reynold
Published: September 2023

Subgraphs are obtained by extracting a subset of vertices and a subset of edges from the associated original graphs, and many graph properties are known to be inherited by subgraphs. Subgraphs can be applied in many areas such as social networks, recommender systems, biochemistry and fraud discovery. Researchers from various communities have paid a great deal of attention to investigate numerous subgraph problems, by proposing algorithms that mainly extract important structures of a given graph. There are however some limitations that should be addressed, with regard to the efficiency, effectiveness and scalability of these traditional algorithms. As a consequence, machine learning techniques---one of the most latest trends---have recently been employed in the database community to address various subgraph problems considering that they have been shown to be beneficial in dealing with graph-related problems. We discuss learning-based approaches for four well known subgraph problems in this tutorial, namely subgraph isomorphism, maximum common subgraph, community detection and community search problems. We give a general description of each proposed model, and analyse its design and performance. To allow further investigations on relevant subgraph problems, we suggest some potential future directions in this area. We believe that this work can be used as one of the primary resources, for researchers who intend to develop learning models in solving problems that are closely related to subgraphs.
Data and AI Model Markets: Opportunities for Data and Model Sharing, Discovery, and Integration
Authors: Pei Jian , Fernandez Raul Castro , Yu Xiaohui
Published: September 2023

The markets for data and AI models are rapidly emerging and increasingly significant in the realm and the practices of data science and artificial intelligence. These markets are being studied from diverse perspectives, such as e-commerce, economics, machine learning, and data management. In light of these developments, there is a pressing need to present a comprehensive and forward-looking survey on the subject to the database and data management community. In this tutorial, we aim to provide a comprehensive and interdisciplinary introduction to data and AI model markets. Unlike a few recent surveys and tutorials that concentrate only on the economics aspect, we take a novel perspective and examine data and AI model markets as grand opportunities to address the long-standing problem of data and model sharing, discovery, and integration. We motivate the importance of data and model markets using practical examples, present the current industry landscape of such markets, and explore the modules and options of such markets from multiple dimensions, including assets in the markets (e.g., data versus models), platforms, and participants. Furthermore, we summarize the latest advancements and examine the future directions of data and AI model markets as mechanisms for enabling and facilitating sharing, discovery, and integration.
Full-Power Graph Querying: State of the Art and Challenges
Authors: Manolescu Ioana , Mohanty Madhulika
Published: September 2023

Graph databases are enjoying enormous popularity, through both their RDF and Property Graphs (PG) incarnations, in a variety of applications. To query graphs, query languages provide structured, as well as unstructured primitives. While structured queries allow expressing precise information needs, they are unsuited for exploring unfamiliar datasets, as they require prior knowledge of the schema and structure of the dataset. Prior research on keyword search in graph databases do not suffer from this limitation. However, keyword queries do not allow expressing precise search criteria when users do know some.

This tutorial (1.5 hours) builds a continuum between structured graph querying through languages such as SPARQL and GPML, a recently proposed standard for PG querying, on one hand, and graph keyword search, on the other hand. In this space between querying and information retrieval, we analyze the features of modern query languages that go toward unstructured search, discuss their strength, limitations, and compare their computational complexity. In particular, we focus on (i) lessons learned from the rich literature of graph keyword search, in particular with respect to result scoring; (ii) language mechanisms for integratingbothcomplex structured querying and powerful methods to search for connections users do not know in advance. We conclude by discussing the open challenges and future work directions.
QO-Insight: Inspecting Steered Query Optimizers
Authors: Anneser Christoph , Petruccelli Mario , Tatbul Nesime , Cohen David , Xu Zhenggang , Pandian Prithviraj , Laptev Nikolay , Marcus Ryan , Kemper Alfons
Published: September 2023

Steered query optimizers address the planning mistakes of traditional query optimizers by providing them with hints on a per-query basis, thereby guiding them in the right direction. This paper introduces QO-Insight, a visual tool designed for exploring query execution traces of such steered query optimizers. Although steered query optimizers are typically perceived as black boxes, QO-Insight empowers database administrators and experts to gain qualitative insights and enhance their performance through visual inspection and analysis.
CEDA: Learned Cardinality Estimation with Domain Adaptation
Authors: Wang Zilong , Zeng Qixiong , Wang Ning , Lu Haowen , Zhang Yue
Published: September 2023

Cardinality Estimation (CE) is a fundamental but critical problem in DBMS query optimization, while deep learning techniques have made significant breakthroughs in the research of CE. However, apart from requiring sufficiently large training data to cover all possible query regions for accurate estimation, current query-driven CE methods also suffer from workload drifts. In fact, retraining or fine-tuning needs cardinality labels as ground truth and obtaining the labels through DBMS is also expensive. Therefore, we propose CEDA, a novel domain-adaptive CE system. CEDA can achieve more accurate estimations by automatically generating workloads as training data according to the data distribution in the database, and incorporating histogram information into an attention-based cardinality estimator. To solve the problem of workload drifts in real-world environments, CEDA adopts a domain adaptation strategy, making the model more robust and perform well on an unlabeled workload with a large difference from the feature distribution of the training set.
Sniffer: A Novel Model Type Detection System against Machine-Learning-as-a-Service Platforms
Authors: Ma Zhuo , Yang Yilong , Xiao Bin , Liu Yang , Liu Xinjing , Ma Zhuoran , Yang Tong
Published: September 2023

Recent works explore several attacks against Machine-Learning-as-a-Service (MLaaS) platforms (e.g., the model stealing attack), allegedly posing potential real-world threats beyond viability in laboratories. However, hampered by
model-type-sensitive
, most of the attacks can hardly break mainstream real-world MLaaS platforms. That is, many MLaaS attacks are designed against only one certain type of model, such as tree models or neural networks. As the black-box MLaaS interface hides model type info, the attacker cannot choose a proper attack method with confidence, limiting the attack performance. In this paper, we demonstrate a system, named Sniffer, that is capable of making model-type-sensitive attacks "great again" in real-world applications. Specifically, Sniffer consists of four components: Generator, Querier, Probe, and Arsenal. The first two components work for preparing attack samples. Probe, as the most characteristic component in Sniffer, implements a series of self-designed algorithms to determine the type of models hidden behind the black-box MLaaS interfaces. With model type info unraveled, an optimum method can be selected from Arsenal (containing multiple attack methods) to accomplish its attack. Our demonstration shows how the audience can interact with Sniffer in a web-based interface against five mainstream MLaaS platforms.
Demonstration of OpenDBML, a Framework for Democratizing In-Database Machine Learning
Authors: Ghorbani Mahdi , Shaikhha Amir
Published: September 2023

Machine learning over relational data has been used in several applications. The traditional approach of joining relations first and then training a model on the joined table is time-consuming and requires a significant amount of memory. Recent research has focused on in-database machine learning (in-DB ML) to address this issue; these methods train the models over relations without joining, resulting in a more efficient process. However, such systems have ad-hoc user interfaces and specific data formats, making them challenging to use. To address this problem, this paper presents OpenDBML, a framework for democratizing in-DB ML. OpenDBML offers a Python interface for multiple in-DB ML systems, a set of commonly used datasets, and the ability to add new datasets and in-DB ML systems via both Python and web interfaces. The paper also presents comprehensive demonstration scenarios to illustrate how to use OpenDBML effectively.
Demonstration of SPARQL

ML

: An Interfacing Language for Supporting Graph Machine Learning for RDF Graphs
Authors: Abdallah Hussein , Afandi Waleed , Mansour Essam
Published: September 2023

This demo paper presents KGNet, a graph machine learning-enabled RDF engine. KGNet integrates graph machine learning (GML) models with existing RDF engines as query operators to support node classification and link prediction tasks. For easy integration, KGNet extends the SPARQL language with user-defined predicates to support the GML operators. We refer to this extension as SPARQL

ML

query. Our SPARQL

ML

query optimizer is in charge of optimizing the selection of the near-optimal GML models. The development of KGNet poses research opportunities in various areas spanning KG management. In the paper, we demonstrate the ease of integration between the RDF engines and GML models through the SPARQL

ML

inference query language. We present several real use cases of different GML tasks on real KGs. Using KGNet, users do not need to learn a new scripting language or have a deep understanding of GML methods. The audience will experience KGNet with different KGs and GML models, as shown in our demo video and Colab notebook.
Interpretable Clustering of Multivariate Time Series with Time2Feat
Authors: Bonifati Angela , Buono Francesco Del , Guerra Francesco , Lombardi Miki , Tiano Donato
Published: September 2023

This paper showcases Time2Feat, an end-to-end machine learning system for Multivariate Time Series (MTS) clustering. The system relies on interpretable inter-signal and intra-signal features extracted from the time series. Then, a dimensionality reduction technique is applied to select a subset of features that retain most of the information, thus enhancing the interpretability of the results. In addition, the system enables domain specialists to semi-supervise the process by submitting a small collection of MTS with a target cluster. This process further improves both accuracy and interpretability, by reducing the number of features used by the clustering process. The demonstration shows the application of Time2Feat to various MTS datasets, by creating clusters from MTS datasets of interest, experimenting with different settings and using the approach capabilities to interpret the clusters generated.
Visualizing Spreadsheet Formula Graphs Compactly
Authors: Chen Fanchao , Tang Dixin , Li Haotian , Parameswaran Aditya G.
Published: September 2023

Spreadsheets are a ubiquitous data analysis tool, empowering non-programmers and programmers alike to easily express their computations by writing formulae alongside data. The dependencies created by formulae are tracked as formula graphs, which play a central role in many spreadsheet applications and are critical to the interactivity and usability of spreadsheet systems. Unfortunately, as formula graphs become large and complex, it becomes harder for end-users to make sense of formula graphs and trace the dependents or precedents of cells to check the accuracy of individual formulae and identify sources of errors. In this paper, we demonstrate a spreadsheet formula graph visualization tool, TACO-Lens, developed as a plugin for Microsoft Excel. Our plugin leverages TACO, our framework for compactly and efficiently representing formula graphs. TACO compresses formula graphs using a key spreadsheet property: tabular locality, which means that cells close to each other are likely to have similar formula structures. This compact representation enables end-users to more easily consume complex dependencies and reduces the response time for tracing dependents and precedents. TACO-Lens, our visualization plugin, depicts the compact representation of TACO and supports users in visually tracing dependents and precedents. In this demonstration, attendees can compare the visualizations of different formula graphs using TACO, Excel's built-in dependency tracing tool, and an approach that does not compress formula graphs, and quantitatively compare the different response time of different approaches.