Miracle-dz/UniFAR-FTUs huggingface dataset:
Load Shedding Techniques for Data Stream Management Systems

In recent years, we have witnessed the emergence of a new class of applications that must deal with large volumes of streaming data. Examples include financial data analysis on feeds of stock tickers, sensor-based environmental monitoring, and network traffic monitoring. Traditional database management systems (DBMS) which are very good at managing large volumes of stored data, fall short in serving this new class of applications, which require low-latency processing on live data from push-based sources. Aurora is a data stream management system (DSMS) that has been developed to meet these needs. A DSMS such as Aurora may be subject to higher input rates than its resources can handle. When input rates exceed system capacity, the system will become overloaded and Quality of Service (QoS) at system outputs will fall below acceptable levels. Under these conditions, the system will shed load by selectively dropping tuples, thus degrading the answer, in order to improve the observed latency of the results. In this dissertation, we first define the load shedding problem in data stream management systems and provide a general solution framework which handles the overload problem in a light-weight manner, while minimizing the loss in result accuracy. Then we present additional techniques on top of this basic framework to handle windowed aggregation queries in a way that preserves the subset result guarantee. Due to the distributed nature of stream-based data sources as well as the need for better scalability and fault tolerance, we have recently extended Aurora into Borealis—a larger-scale system that can operate in distributed environments. In such an environment, the load shedding problem involves simultaneously removing excess load from multiple overloaded nodes in a scalable fashion. In the final part of this thesis, we investigate this distributed load shedding problem, and provide several alternative solutions to extend our earlier framework in Aurora to the distributed setting of the Borealis system.
An empirical investigation of knowledge management competence for enterprise resource planning systems success: insights from Jordan

The primary objective of the study reported herein is to empirically test the implicit, positive relationships between ERP-related Knowledge Management Competence (KM-competence; knowledge creation, knowledge retention, knowledge transfer, and knowledge application) dimensions and the extended Enterprise Resource Planning System Success construct (ERP system success; individual impact, workgroup impact, organisational impact, information quality, system quality, and vender/consultant quality). Data were collected from 173 of business and IT managers in 455 organisations in Jordan. Statistical techniques employed included confirmatory factor analysis to examine validity of the measurement model, and structural equation modelling using AMOS 16.0 is also utilised to test the hypotheses. The results of analysis show there is a positive significant impact of ERP knowledge creation on ERP success. Also, ERP knowledge retention positively and significantly affects ERP system success. Moreover, ERP knowledge transfer positively and significantly influence ERP system success. Furthermore, ERP knowledge application has positive effect on ERP system success. The results also indicate that ERP success construct is robust since all six observed variables are strongly loaded to the latent variable. Research limitations as well as implications for practice and research are discussed.
Affirmation and Action: A Posthumanist Feminist Agenda for Archaeology

This paper explores the potential of posthumanist feminism in archaeology. We find ourselves exhausted in the face of the continuing inequalities in our discipline and the volatile political times we live in, where discrimination and xenophobia, entangled with the patriarchy, create a toxic mix. In the face of this, we draw inspiration from ongoing activism within archaeology and the emergence of posthumanist feminism beyond archaeology. We consider the juxtaposition between activism in the discipline and the lack of engagement with the same issues in our theory. Posthumanist feminism is explored as a way to unite theory and activism. It connects to and builds on existing feminisms but is argued to differ in three ways: first, posthumanist feminism widens the scope of those for whom we should be working to achieve equality; second, it suggests radical shifts in our ontology are necessary to bring about equality; third, it develops an alternative approach to difference. We explore the potential for posthumanist feminism to reshape narratives about the past, the way we do archaeology, and archaeological activism. In each, the aim is to turn away from the majoritarian subject and to make space for multiple alternative voices to emerge and thrive in archaeology.
Uplink Spectral Efficiency of Large, Distributed Antenna Systems With MMSE Processing

The spectral efficiency of a representative uplink in a wireless network with spatially distributed antennas and linear minimum-mean-square-error processing is found to approach an asymptote with a simple form as the number of antennas increases. These results generalize prior work which was applicable to systems with small numbers of base stations with large numbers of antennas each, to systems with large numbers of spatially distributed access points with small numbers of antennas each, and systems between these extremes. Additionally, these results are applied to systems where mobiles have multiple transmit antennas, and are used to characterize systems with both disjoint and user-centric clustering of cooperating base stations. Among other conclusions, these results indicate that with the same density and number of antennas cooperating to serve a mobile user, the uplink spectral efficiency with all antennas randomly distributed is several-fold higher than the case when the antennas are concentrated at one base station. These findings help improve our understanding of the tradeoffs involved in distributed antenna systems which have the potential to significantly increase data rates, but at a higher cost.
Testicular Macrophages Produce Progesterone De Novo Promoted by cAMP and Inhibited by M1 Polarization Inducers

Tissue-resident macrophages (Mø) originating from fetal precursors are maintained via self-renewal under tissue-/organ-specific microenvironments. Herein, we developed a propagation method of testicular tissue-resident Mø in mixed primary culture with interstitial cells composed of Leydig cells from the mouse testis. We examined Mø/monocyte marker expression in propagated testicular Mø using flow cytometry; gene expression involved in testosterone production as well as spermatogenesis in testicular Mø and interstitial cells propagated by mixed culture via RT-PCR; and progesterone (P4) de novo production in propagated testicular Mø treated with cyclic adenosine monophosphate, isoproterenol, and M1 polarization inducers using ELISA. Mø marker expression patterns in the propagated Mø were identical to those in testicular interstitial Mø with a CD206-positive/major histocompatibility complex (MHC) II-negative M2 phenotype. We identified the genes involved in P4 production, transcription factors essential for steroidogenesis, and androgen receptors, and showed that P4 production de novo was upregulated by cyclic adenosine monophosphate and β2-adrenergic stimulation and was downregulated by M1 polarization stimulation in Mø. We also demonstrated the formation of gap junctions between Leydig cells and interstitial Mø. This is the first study to demonstrate de novo P4 production in tissue-resident Mø. Based on previous studies revealing inhibition of testosterone production by P4, we propose that local feedback machinery between Leydig cells and adjacent interstitial Mø regulates testosterone production. The results presented in this study can facilitate future studies on immune-endocrine interactions in gonads that are related to infertility and hormonal disorders.
Dietary Patterns and Their Association with Sociodemographic and Lifestyle Factors in Filipino Adults

Recent studies have investigated dietary patterns to assess the overall dietary habits of specific populations. However, limited epidemiological research has been conducted to explore the unique dietary intakes in low and middle-income countries. This study aims to examine the dietary patterns of Filipino adults and their association with sociodemographic and lifestyle factors. A total of 10,025 adults (≥20 years old) who participated in the 2013 Philippine National Nutrition Survey were included in the analysis. Dietary patterns were derived using factor analysis of 18 food groups from the dietary survey component. Six dietary patterns were identified, namely (1) rice; (2) cereal, milk, sugar, and oil; (3) fruits and miscellaneous food; (4) fish; (5) vegetables and corn; and (6) meat and beverage. Generalized ordered logistic regression analysis indicated that the dietary patterns were associated with different factors, specifically sex, age, educational attainment, marital status, employment status, household size, wealth quintile, smoking status, alcohol consumption, and physical activity. Our findings showed distinct dietary patterns among Filipino adults that were influenced by various sociodemographic and lifestyle parameters. The results of this study have valuable public health implications and the dietary patterns generated can further be used to analyze the link between diet and health outcomes.
Ethnicity, Social, and Clinical Risk Factors to Tooth Loss among Older Adults in the U.S., NHANES 2011–2018

Background. Many older adults suffer from poor oral health, including tooth loss, and disparities among racial/ethnic and socially disadvantaged populations continue to exist. Methods. Data were obtained from the National Health and Nutrition Examination Survey among the adult population in the U.S. The prevalence of edentulism and multiple regression models were conducted on 15,821 adults, including Asians, Blacks, Hispanics, Whites, and others to assess the relationships between tooth loss and their predictors. Results. The prevalence of complete tooth loss increased with age from 0.7% for ages 20–44 to 20.2% for ages 65 and over. There are disparities in complete tooth loss regarding race/ethnicity, with the highest percentages (9%) among Whites and Blacks and the lowest percentages among Asians (3%) and Hispanics (4%). After adjusting for predictors, their impact on tooth loss was not consistent within racial/ethnic groups, as Asians had more tooth loss from Model 1 (β = −1.974, p < 0.0001) to Model 5 (β = −1.1705, p < 0.0001). Conclusion. Tooth loss was significantly higher among older adults and racial/ethnic groups even after controlling for other predictors among a nationally representative sample. The findings point to the fact that subgroup-tailored preventions are necessary.
Luminescent Lifetime Regulation of Lanthanide-Doped Nanoparticles for Biosensing

Lanthanide-doped nanoparticles possess numerous advantages including tunable luminescence emission, narrow peak width and excellent optical and thermal stability, especially concerning the long lifetime from microseconds to milliseconds. Differing from other shorter-lifetime fluorescent nanomaterials, the long lifetime of lanthanide-doped nanomaterials is independent with background fluorescence interference and biological tissue depth. This review presents the recent advances in approaches to regulating the lifetime and applications of bioimaging and biodetection. We begin with the introduction of the strategies for regulating the lifetime by modulating the core–shell structure, adjusting the concentration of sensitizer and emitter, changing energy transfer channel, establishing a fluorescence resonance energy transfer pathway and changing temperature. We then summarize the applications of these nanoparticles in biosensing, including ion and molecule detecting, DNA and protease detection, cell labeling, organ imaging and thermal and pH sensing. Finally, the prospects and challenges of the lanthanide lifetime regulation for fundamental research and practical applications are also discussed.
Ultrasound-Assisted and Microwave-Assisted Extraction, GC-MS Characterization and Antimicrobial Potential of Freeze-dried L. Camara Flower

Lantana camara is known to have anti-bacterial properties which can be exploited to develop a natural food preservative. There is huge demand for natural preservatives in food industry due to the increased health risks associated with synthetic preservatives, development of effecient extraction methods are essential to retain heat sensitive bioactive compounds. This aim of this study was to compare the performance of microwave-assisted extraction (MAE), ultrasound-assisted extraction (UAE), and conventional solvent extraction (CSE) methods for extraction of freeze-dried lantana flower. The phytochemicals in freeze-dried flowers were characterized by GC-MS analysis and antibacterial properties were tested at different concentrations (50, 100, and 150 µl) against E.coli, Salmonella, and S. aureus. It was evident that the UAE offered the highest yield (64%), followed by MAE (53%) and CSE (49%) with distilled water as solvent. The freeze-dried extract possessed a high amount of tannins (417 µg/g), followed by flavonoids such as catechol (88 µg/g) and quercetin (9.2 µg/g). The antibacterial potential results revealed that only distilled water-based extraction techniques offered positive inhibition zones of 2.0-2.67 mm (MAE), 1.67-2.67 mm (UAE), and 1.67-2.17 mm (CSE) against all three organisms, while the chloroform based extracts had no inhibition effect. The microwave-assisted extract at 150 µl concentration offered a significant inhibitory effect against all three pathogens. The GC-MS profiling of bioactive compounds in flower extract revealed the presence of hexadecanoic acid as the major phytochemical compound in all three extraction techniques. The study revealed that the chloroform extract failed to exhibit an antibacterial effect due to the absence of alkaloids, saponins, and anthraquinones as a result of its neutralizing effect.
Nexus Between Real Exchange Rate Misalignment and Economic Growth: A Case of Pakistan

This study investigates the nexus between real effective exchange rate (REER) misalignment and the economic growth of Pakistan. It relies on a single equation model for estimating equilibrium exchange rate using the autoregressive distributive lags (ARDL) approach. The study further uses the growth equation to explore the effects of misalignment of RER on growth proxies. The data were obtained from the official websites of the World development indicator, IMF, Penn World Table, Pakistan Bureau of Statistics, and Ministry of Finance Pakistan. In terms of trade, the data was available on three different bases in different editions of the economic survey of Pakistan. All unit values of imports and exports were changed as per new base 1991 so that the data from editions of survey becomes uniform. The study takes data from 1970 to 2020. The study findings show that gross capital formation, trade openness, and government spending have a substantial role in defining the equilibrium REER. The findings also identify a positive and significant effect of REER misalignment on the economic growth of Pakistan. This paper contributes by measuring the degree of misalignment of real exchange rates using the single equation approach which is rare in the case of Pakistani literature. The single equation approach not only measures the misalignment by PPP factor but also considers basic economic fundamentals such as trade openness, terms of trade, productivity differentials etc. The study further provides evidence of misalignment with economic growth over a longer period (1970-2020). The findings suggest the effective use of exchange rate policy to control exchange rate misalignment to get higher and more sustainable economic growth. The study is useful for policymakers in the long-term economic planning of Pakistan. The results can be generalized for other economies with similar features.
Dental Tissue as a Source of Stem Cells: Perspectives for Teeth Regeneration

Stem cells are defined as cells that have the self-renew capacity and the ability to differentiate into one or more cell types. Recently, stem cell biology has become an interesting topic, especially because of the potential to use it in regenerative medicine. Several types of human stem cells have been isolated and identified in vivo and in vitro . This review highlights the characteristics and therapeutic potential of human dental progenitor/stem cells.
Experimental and modeling studies of the plasma chemistry in a humid Ar radiofrequency atmospheric pressure plasma jet

While humid atmospheric pressure plasmas are extensively modeled, reaction set validation for these conditions remains limited. We present a detailed comparison of a modelling and experimental study with a goal to elucidate the plasma chemistry in a humid Ar radiofrequency-driven atmospheric pressure plasma jet. A large group of species including radicals (H, OH, O, HO2) and long-lived species (H2, O2 and H2O2) in the jet effluent was experimentally quantified by molecular beam mass spectroscopy (MBMS). MBMS measurements of H2O2, OH and H were validated by direct comparison with a liquid phase colorimetric measurement, laser-induced fluorescence (LIF) and two-photon absorption LIF respectively. While an excellent agreement was found for OH and H2O2 by both techniques, a significant difference was found for H and shown to be due to boundary layer effects at the MBMS sampling substrate. The measured O, OH, HO2 and H2 are in good agreement with the plug model while H and O2 were underestimated and H2O2 was overestimated by the model. The accuracy of both the used reaction set and the diagnostics, as well as the observed discrepancies between the modeling and experimental results, are critically assessed. The results presented in this work enable us to identify further data needs for describing H2O vapor chemistry in low-temperature plasmas.
Knowledge, Attitudes, and Use of Protein Supplements among Saudi Adults: Gender Differences

Saudi Arabia has witnessed recent reforms and positive socio-political changes that have led to increased opportunities for women to participate in fitness centers. This study investigated protein supplement consumption among Saudi females compared with that among males and examined the knowledge and attitudes of the participants toward protein supplement use. A cross-sectional study was conducted in Riyadh using a previously validated, self-administered online survey. The questionnaire included items related to the prevalence, knowledge, attitudes, and practice of protein supplementation. The participants were 354 adults (58.2% were females). The results showed that over 47% of the participants attended fitness centers with more male (80.3%) than female (41%) attendees. Nearly 50% of the participants consumed protein supplements, with males (68.7%) using significantly (p < 0.001) more protein supplements than females (35.6%). The powdered form was most commonly consumed. The percentage of gym attendees (67.8%) who used protein supplements was higher than that among non-gym attendees (32.2%). Gaining muscles (56.1%) followed by compensating for protein deficiency (28.6%) were the reasons for taking protein supplements, with a significant gender difference (p < 0.001). Coaches provided the most information on protein supplements. The participants appeared to be knowledgeable about protein supplements. Although over 68% of protein supplement users suffered from various symptoms, only 20% of the participants thought that there was no risk in taking protein supplements, with significant gender differences. It was concluded that Saudi male participants are twice more likely to attend the gym and consume protein supplements compared with females. Of both genders, those attending the gym consumed more protein supplements than non-gym attendees.
Student Performance Prediction Model for Predicting Academic Achievement of High School Students

Modern technology is necessary and important for improving the quality of education. While machine learning algorithms to support students remain limited. Thus, it is necessary to inspire educational scholars and educational technologists. This research therefore has three main targets: to educate the holistic context of rural education management, to study the relationship of continuing education at the upper secondary level, and to construct an appropriate education program prediction model for high school students in a rural school. The data for research is the academic achievement data of 1,859 students from Manchasuksa School at Mancha Khiri District, Khon Kaen Province, Thailand, during the academic year 2015-2020. Research tools are separated into 2 sections. The first section is a basic statistical analysis step, it composes of frequency analysis, percentage analysis, mean analysis, and standard deviation analysis. Another section is the data mining analysis phase, which consists of discretization technique, XGBoost classification technique (Decision Tree, Gradient Boosted Trees, and Random Forest), confusion matrix performance analysis, and cross-validation performance analysis. At the end, the research results found that the reasonable distribution level of student achievement consisted of four clusters classified by academic achievement. All four clusters were modeled on predicting academic achievement for the next generation of students. In addition, there are four success models in this research. For future research, the researcher aims to develop an application to facilitate instruction for learners by integrating prediction models into the mobile application to promote the utilization of modern technology.
DSWEmod — The Production of High‐Frequency Surface Water Map Composites from Daily MODIS Images

Optical satellite imagery is commonly used for monitoring surface water dynamics, but clouds and cloud shadows present challenges in assembling complete water time series. To test whether the daily revisit rate of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery can reduce cloud obstruction and improve high‐frequency surface water mapping, we compared map results derived from Landsat (30‐m) and MODIS (250‐m) data across the state of California for 2003–2019. We adapted the Dynamic Surface Water Extent (DSWE) model in Google Earth Engine to generate surface water map composites from MODIS imagery every 5, 10, 15, and 30 days, and compared products to monthly Landsat‐based DSWE maps. Results for DSWEmod (DSWE MODIS) in California suggest that more than 5% data loss (cloud obstruction, etc.) was present in only 2% of the 15‐day time series, as compared to 32% of the monthly Landsat DSWE time series. The five‐day DSWEmod composites averaged 8.4% obscuration in the winter months. Area estimates derived from cloud‐filtered MODIS and Landsat monthly products have the highest linear correlations compared to streamgage discharge records, suggesting that monthly scale analyses best explain the relationship between surface water area and general streamflow dynamics. Shorter‐interval DSWEmod products have lower correlations but utility for understanding the timing of surface water peaks and past flood events.