bluuebunny/crossref_metadata_2025 huggingface dataset:
Processamento de Imagens dos Satélites Brasileiros CBERS-4 e CBERS-4A para Respostas Rápidas a Desastres
Authors: Rocha Brenda Oliveira , Körting Thales Sehn , Namikawa Laercio Massaru
Published: August 2024

As imagens de satélite podem contribuir para a identificação e análise das áreas afetadas por desastres naturais, através da utilização de técnicas de Processamento Digital de Imagens (PDI) que ressaltam áreas de interesse. O International Charter “Space and Major Disasters” é a principal cooperação mundial entre agências espaciais para o fornecimento gratuito de dados de emergência e conta com o Brasil no processo de resposta aos chamados. Dando importância para as solicitações de emergência, a presente pesquisa propõe a utilização dos satélites brasileiros para sistematizar técnicas de PDI como auxílio à gestão de desastres do tipo deslizamentos de terra e inundações regionais. Apresentamos dois casos de estudo: os deslizamentos em Petrópolis (RJ), ocorridos em 2022, e as inundações regionais em três províncias do Paquistão, de 2022. A mineração de dados realizada com o apoio do algoritmo Random Forest (RF) foi adotada para extrair os principais atributos que posteriormente foram combinados no espaço de cores RGB para a identificação rápida das áreas atingidas. A composição de cores proposta para Petrópolis foi baseada na seleção de uma componente principal, índice de vegetação e componente matiz da transformação de cores IHS, com uma Acurácia Global (AG) de 81,82%, obtida a partir dos dados do MUX/CBERS-4A. A composição sugerida para o Paquistão foi baseada na seleção da banda NIR e da primeira e segunda componente principal, com uma AG de 88,33%, utilizando imagens do WFI/CBERS-4. Todas as áreas de interesse puderam ser evidenciadas com bom êxito a partir das composições sugeridas.
FAKTOR-FAKTOR INTERNAL RESILIENSI PENYANDANG DISABILITAS BARU KORBAN BENCANA GEMPA BUMI DI PROVINSI DIY
Authors: Hanjarwati Astri
Published: August 2024

This article discusses the internal factors of resilience for people with new disabilities who are victims of the earthquake disaster. This research was conducted using a quantitative and qualitative approach (mix method). There were 124 respondents who were involved in this study consisting of people with new disabilities and their families who came from six sub-districts in Bantul Regency. Data was collected by conducting surveys of new persons with disabilities and interviewing families of persons with disabilities. The data that has been collected is then analyzed using SPSS analysis for survey results and coding for interview results. The results of the study show that the internal factors that influence people with disabilities to become resilient are adaptability, problem-solving skills, high optimism, good relationship building skills, and skills to contribute to society.
Keywords: Internal factor, earthquakes, people with new disabilities, resilience.
SURVIVAL STRATEGIES FOR MSME’S DURING COVID 19 IN EAST JAVA INDONESIA
Authors: Mariana Mariana , Hariyati Hariyati , Wuryani Eni , Handayani Susi , Putikadea Insyirah , Abdullah Azizah Binti
Published: August 2024

Globally, the impact of Covid-19 has destructed business supply chains, dropped commodity prices, and increased the risk of global economic. Domestically in Indonesia, the impact of Covid -19 caused business closing, travel banning and reduction in discretionary spending. On September 2020, Bisnis Liputan6 highlighted Micro, Small and Medium Enterprises (MSMEs) as one of the main drivers of the economy in Indonesia (Liputan6.com, 2020). If the MSMEs sector is disrupted, the national economy will be also affected. Thus, this indicates the need for MSMEs to continue its operation. Suci (2017) emphasises the ability of MSMEs to survive during the crisis period of 1997-1998. The MSMEs were able to create millions of jobs until 2012. During the Corona Covid-19 pandemic, the MSME sector was most affected. Many of these entrepreneurs had to go out of business because demand fell. This study aims to identify MSMEs’ survival strategy and  business performance during Covid-19 in Surabaya, East Java Indonesia. This research is a quantitative approach.The data were collected using questionnaire survey. The population and sample in this study were MSMEs in Surabaya. Results indicate MSME believe that future online business is growing. The results also suggest  MSMEs must adapt and take advantage of technology and product and services innovation. MSMEs business strategy during a pandemic is to maintain existing market share. Overall results show that the survival strategies have effect on business performance.
THE EFFECT OF GREEN ACCOUNTING PRACTICE ON MAQASHID SHARIA PERFORMANCE IN ISLAMIC BANKS
Authors: Khasanah Amirah Arifah , Laela Sugiyarti Fatma
Published: August 2024

The purpose of this study is to analyze the effect of green accounting practice on maqashid sharia performance in Islamic banks. This research data used secondary data of 16 Islamic banks in Indonesia. Smart PLS 4 with the SEM-PLS model is the software used to test the effect between the dependent variable, namely the maqashid sharia index which is proxied in educating individuals; establishing justice; and promoting welfare on the independent variable, namely green accounting practice which is also proxied by green investment, green initiatives, and green activity management. Meanwhile, the control variables used in this study aim to control causality in obtaining a more complete empirical model measured using bank size. The results indicate that green investment, green initiative, and green activity management that fulfil the category in representing the practice of green accounting in islamic banks. The implementation of maqashid sharia in Islamic banks is only represented by educating individuals and promoting welfare. Furthermore, the results of the effect test in this study are green accounting practice have a negative significant effect on maqashid sharia performance in islamic banks. While bank size proxied as control variable have a positive significant effect on maqashid sharia performance.
The Relationship Between the Duration of Kangaroo Mother Care and Edinburgh Postnatal Depression Scale Outcomes in Mothers with Preterm Infants
Authors: Pranoto Ivena Celia Eileen , Suswihardhyono Adhie Nur Radityo , Wardani Natalia Dewi
Published: August 2024

Background: Preterm birth has a negative impact on the health of the baby and increases the risk of postpartum depression in mothers. Kangaroo mother care (KMC) is a preterm baby care which is considered to increase bonding between mother and baby, thereby reducing the incidence of postpartum depression, which can be evaluated using the Edinburgh Postnatal Depression Scale (EPDS) instrument.Objective: To find out the relationship between the duration of KMC and EPDS outcomes in mothers with preterm infants.Methods: This study used a quasi-experimental method with non-randomized control group pre-test and post-test design and was conducted on 34 mothers with preterm infants who gave birth at Dr. Kariadi Hospital Semarang. The research subjects were selected using consecutive sampling method and were asked to perform kangaroo mother care for 60 minutes daily (control group) and 120 minutes daily (treatment group) for 14 days. Evaluation was carried out using the Edinburgh Postnatal Depression Scale questionnaire, which was completed twice, as a pre-test and post-test. Data analysis was performed using paired sample T-test and independent samples T-test to determine the relationship between variables.Results: Results showed that there was a significant relationship between the duration of KMC and EPDS outcomes. The difference between the decreased of EPDS scores in the control and treatment groups was significant (p=0.017). The significant decrease of EPDS score was found in the treatment group (p<0.001). The decrease of EPDS score in the control group was not significant (p=0.704).Conclusion: Increasing duration of KMC lowers the score of EPDS in mothers with preterm infants.
ANALYSIS OF ACTIVITY BASED COSTING AS THE BASIS FOR INPATIENT SERVICES TARIFF AT INTAN MEDIKA LAMONGAN HOSPITAL
Authors: Munaa Nihayatul , Rahmawati Nahardian Vica , Nurdiana Fara , Kusdiyana Ari , Kusbiantoro Dadang , Sholihah Enny Mar’atus
Published: August 2024

Activity Based Costing is a cost assignment system based on the activities carried out by the company to produce products. The aim of this research is to find out and obtain information about calculating and comparing prices for inpatient room rates using conventional cost calculation methods with the ABC method. This is the quantitative descriptive research involves conducting interviews with the person in charge of the VIP inpatient room and financial department who relates to the research data. The results of the research show that the calculation of inpatient service rates using the Activity Based Costing method for the VIP class is IDR 160,499. From these results, when compared with the tariff used by Intan Medika Hospital of IDR 266,000, the Activity Based Costing method provides cheaper results with a difference of IDR 105,501. So by reducing rates according to the Activity Based Costing method, Intan Medika Hospital can expand its market because if it uses more appropriate prices and provides good quality, customers will choose to use Intan Medika Lamongan Hospital, so that Intan Medika Lamongan Hospital can increase the occupancy of VIP inpatient room and have a long-term profits.
Efficient Index for Temporal Core Queries over Bipartite Graphs
Authors: Tian Anxin , Zhou Alexander , Wang Yue , Jian Xun , Chen Lei
Published: August 2024

Many real-world binary relations can be modelled as bipartite graphs, which can be inherently temporal and each edge is associated with a timestamp. The (
α, β
)-core, a popular structure that requires minimum degrees over two layers of vertices, is useful for understanding the organisation of bipartite networks. However, the temporal property has rarely been considered in cohesive subgraph mining in bipartite graphs. This gap prevents the finding of time-sensitive (
α, β
)-cores in real-world applications. In this paper, we aim at finding (
α, β
)-cores within any time window over a temporal bipartite graph. To address this problem, we propose a novel DAG (Directed Acyclic Graph)-like hierarchy with qualified time windows to describe the temporal containment property of the (
α, β
)-core. Furthermore, we construct the superior-optimized index which significantly optimizes space complexity and guarantees efficient query performance. We also propose a maintenance approach that can efficiently update the index by removing stale information and incorporating newly inserted temporal edges. Extensive experiments are conducted on eight real-world graphs and the results show the effectiveness and efficiency of our indexes.
Ensemble Clustering Based on Meta-Learning and Hyperparameter Optimization
Authors: Treder-Tschechlov Dennis , Fritz Manuel , Schwarz Holger , Mitschang Bernhard
Published: August 2024

Efficient clustering algorithms, such as
k
-Means, are often used in practice because they scale well for large datasets. However, they are only able to detect simple data characteristics. Ensemble clustering can overcome this limitation by combining multiple results of efficient algorithms. However, analysts face several challenges when applying ensemble clustering, i. e., analysts struggle to (a) efficiently generate an ensemble and (b) combine the ensemble using a suitable consensus function with a corresponding hyperparameter setting. In this paper, we propose EffEns, an efficient ensemble clustering approach to address these challenges. Our approach relies on meta-learning to learn about dataset characteristics and the correlation between generated base clusterings and the performance of consensus functions. We apply the learned knowledge to generate appropriate ensembles and select a suitable consensus function to combine their results. Further, we use a state-of-the-art optimization technique to tune the hyperparameters of the selected consensus function. Our comprehensive evaluation on synthetic and real-world datasets demonstrates that EffEns significantly outperforms state-of-the-art approaches w.r.t. accuracy and runtime.
Win-Win: On Simultaneous Clustering and Imputing over Incomplete Data
Authors: Sun Yu , Zhu Jingyu , Xu Xiao , Xu Xian , Sun Yuyao , Song Shaoxu , Li Xiang , Yuan Xiaojie
Published: August 2024

Although clustering methods have shown promising performance in various applications, they cannot effectively handle incomplete data. Existing studies often impute missing values first before clustering analysis and conduct these two processes separately. However, inaccurate imputation does not necessarily contribute positively to the subsequent clustering. Intuitively, accurate imputation and clustering can serve and benefit from each other, where clustering-based imputation methods typically utilize cluster signals to impute incomplete data and accurate fillings are expected to bring more valuable data for clustering. Therefore, in this manuscript, rather than considering two tasks independently or conducting them respectively, we study simultaneous clustering and imputing over incomplete data. The immediate benefit is that such a strategy improves both clustering and imputation performance simultaneously, to get a win-win result. Our major technical highlights include (1) the problem formalization and NP-hardness analysis on computing simultaneous clustering and imputing results, (2) exact solutions by transforming the problem as the integer linear programming (ILP) formulation, and (3) efficient approximation algorithms based on the linear programming (LP) relaxation and local neighbors (LN) solution, with approximation guarantees. Experiments on various real-world datasets demonstrate the superiority of our work in clustering and imputing incomplete data.
Efficiently Mitigating the Impact of Data Drift on Machine Learning Pipelines
Authors: Dong Sijie , Wang Qitong , Sahri Soror , Palpanas Themis , Srivastava Divesh
Published: August 2024

Despite the increasing success of Machine Learning (ML) techniques in real-world applications, their maintenance over time remains challenging. In particular, the prediction accuracy of deployed ML models can suffer due to significant changes between training and serving data over time, known as
data drift.
Traditional data drift solutions primarily focus on detecting drift, and then retraining the ML models, but do not discern whether the detected drift is harmful to model performance. In this paper, we observe that not all data drifts lead to degradation in prediction accuracy. We then introduce a novel approach for identifying portions of data distributions in serving data where drift can be potentially harmful to model performance, which we term Data Distributions with Low Accuracy (DDLA). Our approach, using decision trees, precisely pinpoints low-accuracy zones within ML models, especially Blackbox models. By focusing on these DDLAs, we effectively assess the impact of data drift on model performance and make informed decisions in the ML pipeline. In contrast to existing data drift techniques, we advocate for model retraining only in cases of harmful drifts that detrimentally affect model performance. Through extensive experimental evaluations on various datasets and models, our findings demonstrate that our approach significantly improves cost-efficiency over baselines, while achieving comparable accuracy.
Enhancing Accuracy for Super Spreader Identification in High-Speed Data Streams
Authors: Wang Haibo
Published: August 2024

This paper addresses the challenge of identifying super spreaders within large, high-speed data streams. In these streams, data is segmented into flows, with each flow's spread defined as the number of distinct items it contains. A super spreader is characterized as a flow with a notably large spread. Current compact solutions, known as sketches, are designed to fit within the constrained memory of online devices. However, they struggle to accurately track the spread of all flows due to the substantial memory requirement for monitoring a single flow --- a problem exacerbated when numerous flows are involved. To overcome these limitations, this study proposes a more precise sketch-based approach. Our solution introduces an innovative non-duplicate sampler that effectively eliminates duplicates, allowing for accurate post-sampling count of flow spread using only counters. Additionally, it incorporates an exponential-weakening decay technique to highlight large flows, markedly enhancing the accuracy of super spreader identification. We offer a comprehensive theoretical analysis of our method. Trace-driven experiments validate that our approach statistically surpasses existing state-of-the-art solutions in identifying super spreaders. It also demonstrates the lowest time required to restore super spreaders and significantly reduces bandwidth consumption by an order of magnitude when offline restoration is conducted remotely.
Searching Data Lakes for Nested and Joined Data
Authors: Zhang Yi , Chen Peter Baile , Ives Zachary G.
Published: August 2024

Exploratory data science is driving new platforms that assist data scientists with everyday tasks, such as integration and wrangling, to assemble training datasets. Such tools take scientists' work-in-progress data as a
search object
(table or JSON) and find relevant supplementary data from an organizational
data lake
, which can be unioned or joined with the current data. Existing data lake search tools find
single
, relational tables to match or join with a search object. Yet many data science applications revolve around hierarchical data, which can only be matched by creating views that simultaneously
join and transform several
tables in the data lake. In this paper, we extend the Juneau data lake search system [46] for this broader class of matches
at scale.
Our contribution is a
general
framework for efficiently merging ranked results to match hierarchical data, leveraging novel techniques for indexing and sketching, and incorporating existing single-table search techniques and ranking functions. We experimentally validate our methods' benefits and broad applicability using real data from data science computational notebooks. Our results indicate that, with different ranking functions, our approach can return the optimal set of views up to 4.8x faster and 43% more related compared to heuristics, and increase the data domain coverage by up to 28%. In a case study to show the utility of our results to data science downstream tasks, we reduce regression error by up to 6.6%, and improve classification accuracy by up to 19.5%.
Saving Money for Analytical Workloads in the Cloud
Authors: Srivastava Tapan , Fernandez Raul Castro
Published: August 2024

As users migrate their analytical workloads to cloud databases, it is becoming just as important to reduce monetary costs as it is to optimize query runtime. In the cloud, a query is billed based on either its compute time or the amount of data it processes. We observe that analytical queries are either compute- or IO-bound and each query type executes cheaper in a different pricing model. We exploit this opportunity and propose methods to build cheaper execution plans across pricing models that complete within user-defined runtime constraints. We implement these methods and produce execution plans spanning multiple pricing models that reduce the monetary cost for workloads by as much as 56%. We reduce individual query costs by as much as 90%. The prices chosen by cloud vendors for cloud services also impact savings opportunities. To study this effect, we simulate our proposed methods with different cloud prices and observe that multi-cloud savings are robust to changes in cloud vendor prices. These results indicate the massive opportunity to save money by executing workloads across multiple pricing models.
Optimizing Collections of Bloom Filters within a Space Budget
Authors: Mersy Gabriel , Wang Zhuo , Sintos Stavros , Krishnan Sanjay
Published: August 2024

With a single Bloom filter, one can approximately answer set membership queries within a space budget. Practical systems often use collections of Bloom filters to facilitate applications such as data skipping, sideways information passing, and network filtering. While the optimal space-to-accuracy allocation is well-understood for a single filter, jointly optimizing how space is used across a collection of filters is yet to be studied. We pose this problem in the following way: (1) let's assume that each Bloom filter has some likelihood of being queried, and (2) given knowledge of this likelihood, how do we allocate space to minimize the expected false positive rate? In other words, "hot" filters are allocated more space, and "cold" filters are allocated less space. In this paper, we show how to solve this optimization problem. We first develop the concept of a "truncated" Bloom filter and theoretically analyze its false positive rate. We then formulate an optimization problem for a collection of truncated Bloom filters that minimizes the false positive rate across a utility distribution while meeting a strict space budget. Next, we show that the problem is convex and find a fast relaxation. Lastly, we apply our method to data skipping and full-text search, demonstrating its effectiveness across the range of possible space budgets when compared to the state of the art.
Index Advisors on Quantum Platforms
Authors: Kesarwani Manish , Haritsa Jayant R.
Published: August 2024

Index Advisor tools settle for sub-optimal index configurations based on greedy heuristics, owing to the computational hardness of index selection. We investigate here how this limitation can be addressed by leveraging the computing power offered by quantum platforms. Specifically, we present a hybrid Quantum-Classical Index Advisor that judiciously incorporates gate-based quantum computing within a classical index selection wrapper.

Two distinct trade-offs between solution quality and computational complexity are considered. First, index selection is modeled as a Quadratic Unconstrained Binary Optimization problem and solved using the popular Quantum Approximate Optimization Algorithm. The obtained solution is approximate, like greedy, but significantly better in quality while incurring only
O
(log(
L
)) computations, where
L
is the total number of candidate configurations. Second, index selection is modeled as a fully enumerative search and solved using the seminal Grover Search algorithm. A novel quantum oracle is proposed that performs computations on data hosted in the relative phase of a quantum superposition state, and is encoded using only standard quantum gates. This approach identifies, with high probability, the
optimal
index configuration with computations.

We have implemented these two designs using the Qiskit SDK and performed proof-of-concept evaluations on both simulation and hardware platforms. Substantive quality improvements, by a multiplicative factor of 1.5 to 2 and approaching optimality, are obtained as compared to a commercial database engine implementing a greedy approach. Moreover, their quantum resource requirements effectively scale linearly with problem size, an essential feature from a feasibility perspective.
Macroeconomic Observations on Paying for and Funding Universal Basic Income
Authors: Sawyer Malcolm
Published: August 2024

The paper undertakes macroeconomic analysis of Universal Basic Income (UBI). It focuses on issues of paying for and the funding of universal basic income. A number of proposals are examined and the limitations of borrowing and money creation for the funding of UBI are indicated. It is generally argued that funding of UBI should be examined in terms of funding through taxation. The effects of UBI on employment and national output and the macroeconomic limits on the scale on UBI in terms of work force participation and tax rates are investigated.
Development of Aβ and anti-Aβ dynamics models for Alzheimer’s disease
Authors: Cindyawati Cindyawati , Ahmad Faozan , Hardhienata Hendradi , Kartono Agus
Published: August 2024

Alzheimer’s disease is one of the most prevalent types of dementia worldwide. It is caused by the accumulation of amyloid-beta (Aβ) plaques in the brain, disrupting communication pathways and memory. Microglia and astrocytes act as the immune system of the brain, clearing Aβ plaque deposits. However, these cells can lose effectiveness when Aβ plaque accumulation exceeds normal limits, leading to inflammation induced by proinflammatory cytokines. One type of treatment involves anti-Aβ drug therapy. Anti-Aβ drugs are believed to have the ability to reduce Aβ plaque deposits effectively. The mechanism of Aβ plaque accumulation can be explained by ordinary differential equations describing the growth of Aβ monomers. In this study, we aimed to develop a new mathematical model to elucidate the role of the immune system and drug therapy in reducing Aβ plaque deposits. Based on the simulation results, we conclude that the use of anti-Aβ drug therapy can decrease the concentration of Aβ plaque deposits, and the effective treatment duration for Alzheimer’s patients is estimated to be approximately 4 months starting from the time the drug was first administered.
From LIKE/LOVE to habitual: the case of Mainland East and Southeast Asian languages
Authors: Fang Hongmei
Published: August 2024

This paper documents the common grammaticalization path of the LIKE/LOVE constructions into expressing habitual aspect in Mainland East and Southeast Asian languages. The stages and degrees of grammaticalization for the LIKE/LOVE constructions vary cross-linguistically and different stages of evolution co-exist in one and the same language. Based on the synchronic data from a sample of six national languages in that region, it is found that the grammaticalization process in Chinese, Thai, and Lao is advanced while the process in Vietnamese, Khmer, and Burmese is incipient. At the initial stage of their grammaticalization, there are three context-induced intermediate steps of development before the constructions in question are compatible with inanimate subject referents and the habitual meaning becomes the only possible interpretation. At the later stage, languages vary in their combinability with stative verbs and in their possibility of occurring in future temporal context. The common human experience that if one likes/loves doing something, one tends to do it frequently renders it highly unlikely that this grammaticalization pattern is an areal feature confined to Mainland East and Southeast Asia.
Family(jiārénmen) is not a family: a study on the construction of pragmatic identities in the generalization of Internet address term “jiārénmen”
Authors: Wang Junling , Mao Yansheng , Zhao Kaihang
Published: August 2024

This paper examines the generalization of the Internet address term “family” (jiārénmen), a recently emerging phenomenon in language use from the perspective of Pragmatic Identity Theory. The main thrust of this research is to reveal the pragmatic identities and pragmatic functions involved in the use of “family” (jiārénmen). The core point has been arrived at by using a combination of quantitative and qualitative analyses to explore relevant cases collected from WeChat, Weibo, and in-person conversations. Research findings demonstrated that in different contexts, the address term “family” (jiārénmen) can construct various pragmatic identities, all of which belong to the deviational identity opposite to the default identity. Notably, the construction of these identities functions to patch up address terms slot, promote relationships, and satisfy transactional needs. Furthermore, the generalization of the address term “family” (jiārénmen) mirrors the effect of the psychological mechanism of communicators and the Chinese family culture on discourse practice. The findings above contribute to extending the research line of Internet address term generalization, as well as a deeper understanding of the mechanism of the Internet address term “family” (jiārénmen) towards a harmonious language-using environment.
Influence of thinner flaked Al powder with larger diameter on the distribution of B4C particles and tensile properties of B4C/Al composite
Authors: Shi Wenchao , Tang Min , Duan Qiangzhi , Gong Dongmei , Xu Feng
Published: August 2024

The thinner flaked Al powders are used to improve the strength of the B4C/Al composite. The effect of the flaked Al powder on distribution of B4C particles is investigated. The tensile properties of the B4C/Al composites with the flaked Al powders are also studied. The results show that during ball milling process, spherical Al powders are flaked with the thinner thicknesses and larger diameters. The thinner flaked Al powders are not easy to be deformed and are bonded together as the laminated structure after thermal compression. B4C particles are evenly dispersed and embedded in Al laminated structure. With increasing the volume fraction of B4C particles, the deformation of the thinner flaked Al powders become difficult and the thinner flaked Al powders coat on the surface of B4C particles, resulting in the disappearance of the laminated structure of the thinner flaked Al powder.
Crystal structure of 4-bromobenzyl 2-(6-methoxy-naphthalen-2-yl)propanoate, C21H19BrO3
Authors: Zhang Xin-Ru , Lin Da-Zhuan , Gao Li-Na
Published: August 2024

C21H19BrO3, orthorhombic, P212121 (no. 19), a = 6.011(2) Å, b = 11.630(2) Å, c = 25.165(5) Å, V = 1759.3(7) Å3, Z = 4, Rgt
(F) = 0.0163, wRref
(F
2) = 0.0420, T = 100(2) K.
Resemblance as a Passing Quality: Liotard, La Tour, and the Question of Le Faire in Eighteenth-Century Portraiture
Authors: Koos Marianne
Published: August 2024

According to Diderot, ressemblance was a central quality in eighteenth-century portraiture – and yet it was ultimately less important than the particular manner of execution, le faire. Bold brushstrokes, art critics agreed in Paris around 1750, not only enliven the subject, but also testify to the artistic enthousiasme, the genius of a painter. While Maurice-Quentin de La Tour perfectly served this ideal with his bravura pastel portraits, his greatest rival at the time, Jean-Étienne Liotard, decidedly turned against this ideal. Concentrating on Liotard’s programmatic painting The Breakfast (exhibited in the Académie de Saint-Luc’s Salon of 1752), this article compares the different pictorial concepts of Liotard and La Tour, illuminates the contemporary discussion on execution, and ultimately asks about the strategies Liotard devised in order not to be overlooked as the author of his paintings despite his smooth finish.
Neuroscientist’s Behavioral Toolbox for Studying Episodic-Like Memory
Authors: Kunčická Daniela , Krajčovič Branislav , Stuchlík Aleš , Brožka Hana
Published: August 2024

Episodic memory, the ability to recall specific events and experiences, is a cornerstone of human cognition with profound clinical implications. While animal studies have provided valuable insights into the neuronal underpinnings of episodic memory, research has largely relied on a limited subset of tasks that model only some aspects of episodic memory. In this narrative review, we provide an overview of rodent episodic-like memory tasks that expand the methodological repertoire and diversify the approaches used in episodic-like memory research. These tasks assess various aspects of human episodic memory, such as integratedwhat–where–whenorwhat–where memory, source memory, free recall, temporal binding, and threshold retrieval dynamics. We review each task’s general principle and consider whether alternative non-episodic mechanisms can account for the observed behavior. While our list of tasks is not exhaustive, we hope it will guide researchers in selecting models that align with their specific research objectives, leading to novel advancements and a more comprehensive understanding of mechanisms underlying specific aspects of episodic memory.
Testosterone therapy-induced erythrocytosis: can phlebotomy be justified?
Authors: Bond Peter , Verdegaal Tijs , Smit Diederik L
Published: August 2024

Erythrocytosis, or elevated hematocrit, is a common side effect of testosterone therapy (TTh) in male hypogonadism. Testosterone stimulates erythropoiesis through an initial rise in erythropoietin (EPO), the establishment of a new EPO/hemoglobin ‘set point’, and a parallel decrease in the master iron regulator protein hepcidin, as well as several other potential mechanisms. Evidence shows an increased thrombotic risk associated with TTh-induced erythrocytosis. Several guidelines by endocrine organizations for the treatment of male hypogonadism recommend against starting TTh in patients presenting with elevated hematocrit at baseline or stopping TTh when its levels cannot be controlled. Besides dose adjustments, therapeutic phlebotomy or venesection is mentioned as a means of reducing hematocrit in these patients. However, evidence supporting the efficacy or safety of therapeutic phlebotomy in lowering hematocrit in TTh-induced erythrocytosis is lacking. In light of this dearth of evidence, the recommendation to lower hematocrit using therapeutic phlebotomy is notable, as phlebotomy lowers tissue oxygen partial pressure (pO2) and eventually depletes iron stores, thereby triggering various biological pathways which might increase thrombotic risk. The potential pros and cons should therefore be carefully weighed against each other, and shared decision-making is recommended for initiating therapeutic phlebotomy as a treatment in patients on TTh who present with increased hematocrit.
KONTESTASI IDENTITAS PERISTIWA “KEMBALI” DALAM NOVEL RAPIJALI KARYA DEE LESTARI
Authors: Kurniawan Heru , Somadayo Samsu Rohman , Sholeh Dwi Rohman , Sutardi Sutardi
Published: August 2024

Returning as the title of the third series of novels, Rapijali by Dee Lestari is the primary key in understanding this novel in psychology and sociology. For this reason, this research was conducted to find and explain the events of Rapijali's identity contestation in a personal and social context so that the meaning of the philosophy conveyed through Rapijali can be understood from a psychological and sociological perspective. The method used is qualitative-textual research that examines the novel Rapjali: Kembali by Dee Lestari by looking at the psychological and sociological aspects using content analysis. Content analysis is related to reviewing aspects of the contestation of the events of Rapijali's return from the personal and social aspects of the characters and correlating them with psychological and sociological contexts. The result of the findings is the contestation of events in Rapijali: Again, it is built on a collective (sociological) consciousness that positions the Rapijali band as a home and family that can lead its members to find achievement and existence. From here, Rapijali is essentially home and a place for members to return to find their real (psychological) family and love. After returning to Rapijali, the end of love and family leads its members to find happiness in love and family in a personal and social context.
Argumentasi Saksi Ahli dalam Sidang Penistaan Agama oleh Basuki Tjahaja Purnama di Kepulauan Seribu
Authors: Subuki Makyun , Erowati Rosida , Sulaiman Agus
Published: August 2024

Ahok's controversial statements on the Thousand Islands seem not only led to massive and repeated demonstrations, but also linguistic debates in the courtroom. This study aims to examine the arguments of linguists who give statements in the courtroom in response to Ahok's statement. As a qualitative study using discourse analysis as a method of analysis, this study uses a critical argumentation approach developed by Walton (2002 and 2006) to examine how the argument was constructed and evaluate the quality of the argument. The analysis in this study indicates that the opinion of linguists presented by public prosecutors is often inconsistent and not based on adequate linguistic evidence, not only inconsistent with other expert statements, but also with his own statement as a scientist. Conversely, the linguist presented by Ahok's counsel is more consistent and more able to present linguistic evidence more adequately.
Roman law on the river ‘Hooghly’: An Excerpt from the history of colonial legal education
Authors: Lacis Victoria
Published: August 2024

British Colonial rule in India led to legal pluralism which colonial civil servants and judges had to deal with in their day-to-day duties. After a brief overview of colonial legal administration in India, this paper will illustrate how future civil servants and judges were educated and prepared for their legal duties in India and what part Roman law played in that. One focus of their legal education lay on the law of property and possession as it assumed particular practical relevance in colonial India. The paper will trace how a Roman rule of property law travelled to Haileybury College in Hertfordshire, England and to the East India Company's courts in India.
Impact of sports enjoyment on academic resilience among student-athletes
Authors: Pasno Aries
Published: August 2024

Background and Study Aim. Previous studies have shown that students who enjoy participating in sports can improve their resilience in academic endeavors. However, such studies are predominantly conducted internationally. Few, if any, focus on the Philippine higher education setting. This study aimed to determine the direct influence of sports enjoyment on academic resilience.
Material and Methods. The respondents in this study are student-athletes from different sports events, currently enrolled in the 1st Semester of the Academic Year 2023-2024 at Bulacan State University in the Philippines. Data were collected using an online survey questionnaire administered via Google Forms. This study employed three separate questionnaires. The first questionnaire gathered demographic characteristics of the respondents. The second part used the Physical Activity Enjoyment Scale-8 (PACES-8). The final part consisted of the Academic Resilience Scale-30 (ARS-30). The relationship between sports enjoyment and academic resilience was measured using Pearson-r. To determine the direct influence of sports enjoyment on academic resilience, simple linear regression was performed.
Results. The findings indicate a positive and significant relationship between the two variables [r(299) = .435, p < .05]. This suggests that when athletes derive great pleasure from their sporting activities, their ability to persevere academically is enhanced. Thus, engaging in sports helps students overcome difficulties in their educational setting and improves their academic achievement. Additionally, sports enjoyment (SE) predicts academic resilience (ARS). This indicates that SE has a direct influence on ARS [F(1, 229) = 53.528, p < .001]. The R² = .189 suggests that the model accounts for 18.9% of the variance in ARS.
Conclusions. Sports enjoyment (SE) can be considered a predictor of academic resilience. Based on the findings, participating in various sports events may significantly boost academic performance and lessen maladjustments in a challenging academic environment.
An analysis of sprint kinematics: the effects of step distance, contact and flight time on sprint performance
Authors: Deliceoğlu Gökhan , Arı Erdal , Tortu Erkan , Keleş Ali
Published: August 2024

Background and Study Aim. Sprinting performance is crucial in many sports, and even marginal improvements in sprint mechanics can provide significant competitive advantages. The aim of this study is to examine the influence of step distance, contact time, and flight time on sprint speed.
Material and Methods. The study was conducted on 26 athletes (20 males and 6 females). Body composition was measured using a bioimpedance analysis device. Sprint kinematics (step distance, contact time, and flight time) and sprint speed parameters were assessed using an optical measurement system during a 30-meter sprint test. Multiple linear regression analysis was employed to determine the effects of sprint kinematic parameters on sprint speed, as well as the effects of body composition parameters on sprint kinematics and speed. The linear regression models included one dependent variable and three independent variables.
Results. Linear regression analysis revealed that step distance, contact time, and flight time were significant predictors of sprint speed, with the exception of the first step of sprint running (p < 0.05). Furthermore, the effects of body composition parameters (age, body weight, and height) on sprint kinematics and speed were found to be significant (p < 0.05). The proportions of variance explained by body composition parameters were highest for step distance and sprint speed, with R2 values of 0.719 and 0.686, respectively.
Conclusions. This study confirms that step distance, contact time, and flight time are significant predictors of sprint speed. Additionally, the results underscore the substantial influence of body composition parameters such as age, body weight, and height on sprint kinematics and speed. These findings highlight the importance of considering both kinematic and physiological factors in the training and development of athletes for optimized sprint performance.
Linear and nonlinear programming: effects on the physical abilities of young basketball players
Authors: Hidayah Taufiq , Akhiruyanto Andry , Haryono Sri , Yudhistira Dewangga
Published: August 2024

Background and Study Aim. Linear and nonlinear programming are methods used to control intensity and volume in sports training. Despite their widespread application, there is a lack of evidence-based studies that directly compare the effects of linear versus nonlinear programming. This study aims to assess the effect of linear and nonlinear programming on improving the power, agility, and endurance of young basketball players.
Material and Methods. This study employs a two-group pretest-posttest experimental design. It included 40 male basketball players aged 16-18, with weights ranging from 60 to 77 kg and heights from 167 to 180 cm. Participants were divided into two groups based on their ordinal pairings. The instruments used in this study were the jump DF, lane agility, and multistage fitness tests. Data were analyzed using descriptive statistics, Wilcoxon tests, and Mann-Whitney U tests, with the assistance of SPSS 23.
Results. The pretest-posttest findings for both the linear and nonlinear programming groups showed significant improvements in power, speed, and endurance, with Asymptotic Significance (Asymp.sig) 2-tailed values of less than 0.05. Comparative analysis of posttest results between linear and nonlinear programming indicated significant differences: power showed an Asymp.sig value of 0.009 with a difference of 3.1; agility showed an Asymp.sig value of 0.000 with a difference of 0.35; and endurance showed an Asymp.sig value of 0.002 with a difference of 2.08.
Conclusions. The study demonstrates significant differences in the impacts of linear and nonlinear programming on power, agility, and endurance among young basketball players. Both programming types significantly enhance these attributes, but nonlinear programming is more effective than linear programming in improving the physical abilities of young basketball players.
Pengaruh Konseling Individu Terhadap Internalisasi Nilai Islam Untuk Pecandu Narkoba
Authors: Fadilah Annisa , Mutaqin Zaenal , Lukman Dede
Published: August 2024

The purpose of the research conducted at Inabah 2 Putri is to find out how much influence individual counseling has on drug addicts, to find out how much influence the internalization of Islamic values has on drug addicts, and to find out how much influence individual counseling has on the internalization of Islamic values for drug addicts. The framework of thought used is individual counseling, internalization of Islamic values and drug addicts. Quantitative method with experimental approach. The results of the study show that 22% is the result of the influence of individual counseling (X1) on drug addicts. Furthermore, 19.2% is the result of the influence of internalizing Islamic values (X2) on drug addicts. And 19.2% is the result of the influence of individual counseling (X1) in the internalization of Islamic values (X2) against drug addicts.
Konsep Epistemologi Perspektif Al-Kindi: Modifikasi Epistemologi Yunani
Authors: Sahidin Amir , Abdurahim Abdurahim
Published: August 2024

Al-Kindi was the first Arab thinker who paid great attention to epistemology. Although al-Kindi adopted many of the epistemological theories of earlier Greek philosophers, al-Kindi's epistemology has fundamental differences and more values due to his belief in Islamic principles. Based on that, this research will discuss the epistemological concept of al-Kindi's perspective. Through a library research study with a descriptive-analytical approach, it can be concluded, first: al-Kindi's epistemological concept is different from the epistemological concept of the Greek philosophers who negate the role of revelation in it. Second, al-Kindi is very concerned with 'illah or the cause of the nature of a science, which includes material, formal, efficient and final causes, all of which begin and end in the cause of al-haq or God. Third, there are three sources of al-Kindi's knowledge, namely the five senses, rational and divine knowledge which is the highest science.
IMPLIKASI FILOSOFIS DESENTRALISASI BITCOIN DALAM PERSPEKTIF EMPIRE NEGRI-HARDT
Authors: Abdul Karim Muhammad Satria , Hadinata Fristian
Published: August 2024

AbstractStudi ini berfokus pada pentingnya memahami implikasi filosofis desentralisasi Bitcoin dalam konteks kebebasan individu. Desentralisasi Bitcoin dipandang sebagai upaya untuk mendapatkan kebebasan finansial dan mengurangi ketergantungan pada institusi pusat. Namun, penelitian ini juga menunjukkan bagaimana kekuatan modal yang merupakan bagian dari sistem kapitalis global dapat memanipulasi dan mengendalikan Bitcoin. Sistem kapitalis global, sering disebut "kerajaan", adalah sebuah realitas di mana kekuasaan didistribusikan di banyak tempat. Desentralisasi Bitcoin menciptakan paradoks, karena kebebasan yang dijanjikan dikompromikan oleh ketidakseimbangan kekuatan yang diciptakan oleh kekaisaran. Oleh karena itu, penelitian ini menggarisbawahi pentingnya kritik filosofis terhadap desentralisasi Bitcoin.
Personal Branding Atlet Muhammad Shohibul Fikri Melalui Instagram
Authors: Al Fiqri Muhammad Rivan , Mukarom Zaenal , Rusmulyadi Rusmulyadi
Published: August 2024

The research was conducted with the aim of knowing the steps for forming Shohibul Fikri's personal branding through Instagram @shohibulfikri. Personal branding can include skills, jobs, routines and so on which will make it easier for someone to recognize because they have their own characteristics. Judgments drawn from other people's thoughts will appear according to what they show. The Authentic Personal Branding model is used by Shohibul Fikri in building his own branding. This research uses a descriptive study approach and uses a constructivist paradigm with the help of primary and secondary data and data collection techniques through unstructured interviews and observation. The results of this study indicate that the personal branding activities carried out by Shohibul Fikri include four steps, namely the stage of showing authenticity, the stage of forming specialization, and the stage of showing persistence. This research resulted in the conclusion that Shohibul Fikri uses Instagram to share content that reflects himself as an accomplished, persistent, and professional young badminton athlete.