Miracle-dz/UniFAR-FTUs huggingface dataset:
Mathematical Scaling and Statistical Modeling of Geopressured Geothermal Reservoirs

The interest for developing geopressured-geothermal reservoirs along the US Gulf Coast is increasing for securing energy needs and reducing global warming. Identifying the most attractive candidate reservoirs for geothermal energy production requires quick and simple models. Analytical models are not always available and simulating each case individually is expensive. The use of scaling and statistical modeling is one approach to translate the output of a simulator into quick models with general applicability at all scales. The developed models can quickly estimate temperature and thermal energy recovery from the geopressured-geothermal reservoirs. These models can screen large databases of reservoirs to select the most attractive ones for geothermal energy production. This study presents two different designs for extracting energy from geopressuredgeothermal reservoirs: Regular line drive and Zero Mass Withdrawal (ZMW). First, the governing partial differential equations describing each design are derived from the fundamental equations. Inspectional analysis on the partial differential equations of each design provides the most succinct and meaningful form of the dimensionless numbers for scaling the designs. The dimensionless numbers are tested and verified by selecting models with identical dimensionless numbers but different dimensional parameters. For creating the response models, statistics is used to find the important dimensionless numbers for predicting the response systematically. A procedure is used to compare possible sub-models and to select the best one. These simplified final models are then presented and assessed using testing runs. Applications of these models are presented. To test the response models, two field cases from southern Louisiana are evaluated: the Gueydan Dome reservoir and the Sweet Lake reservoir. The Gueydan Dome reservoir (Vermilion parish, LA) is investigated using an optimization algorithm and it is concluded that the temperature map should be used for pre-development heat extraction assessments. The Sweet Lake reservoir (Cameron parish, LA) is studied using this conclusion. xiv Chapter
Resilient Cooperative Output Regulation for Nonlinear Multiagent Systems Under DoS Attacks

The resilient cooperative output regulation problem for a class of uncertain nonlinear multiagent systems (MASs) under denial-of-service (DoS) attacks is addressed in this article. This is the first attempt to investigate the cooperative output regulation problem for nonlinear MASs under DoS attacks, and a novel distributed control scheme consisting of a resilient distributed observer and a distributed adaptive controller is proposed. Specifically, a novel resilient distributed observer in the form of an upper triangular chain of first-order low pass filters is designed to estimate the exosystem state based on a composite output observability condition. Then, a distributed adaptive controller is designed. It is shown that the resilient cooperative output regulation problem for the concerned class of uncertain nonlinear MASs can be solved by the proposed control scheme. A simulation example is finally provided to show the effectiveness of the proposed control scheme.
Kangaroo Fathers Modulate Maternal Control of Offspring Sex but Not Postpartum Maternal Expenditure

When sons and daughters have different fitness costs and benefits, selection may favor deviations from an even offspring sex ratio. Most theories on sex ratio manipulation focus on maternal strategies and sex-biased maternal expenditure. Recent studies report paternal influences on both offspring sex ratio and postpartum sex-biased maternal expenditure. We used long-term data on marked kangaroos to investigate whether and how paternal mass and skeletal size, both determinants of male reproductive success, influenced (a) offspring sex in interaction with maternal mass and (b) postpartum sex-biased maternal expenditure. When mothers were light, the probability of having a son increased with paternal mass. Heavy mothers showed the opposite trend. A similar result emerged when considering paternal size instead of mass. Postpartum maternal sex-specific expenditure was independent of paternal mass or size. Studies of offspring sex manipulation or maternal expenditure would benefit from an explicit consideration of paternal traits, as paternal and maternal effects can modulate each other.
Low Cost Oyster Mushroom Production

Bangladesh the 7th populous country continuously looses agricultural lands. So intensive use of land for increasing crop production is a better option but it is very difficult due to natural hazards and other barriers. In this aspect mushroom cultivation may be a better opportunity increasing crop production per unit area by vertical use of land and also meeting the protein demand. So, investigation on low cost mushroom production with high yield and quality using available agro wastes is an urgent demand. Therefore, this book will discuss with oyster mushroom production in low cost, keeping the nutritional value same. A low cost approach, supplementation of sawdust with different supplement, found to be significant in increasing yield, biological efficiency (BE) and benefit cost ratio (BCR). NPK mixed fertilizer (N=0.6%, P=0.3%, K=0.3%) supplemented at 11.5% with sawdust is found promising lowering the production cost, increasing yield and nutritional content of fruiting body. Cow dung (11.5%) and wheat flour (5.5%) as supplement with substrate may be the fair choice. This book will help Farmers, Researchers, Extension workers or any other person interested in this area.
VIDEO POPULARITY PREDICTION USING STACKED BILSTM LAYERS

Social media is now not only limited to being a life event sharing platform, but it also has evolved as a monetary medium. Advertisements showing on popular videos may result in more sales conversion. So it is of utmost interest to predict the popularity of videos before uploading it on the platform. In this research article, we propose a deep learning algorithm to predict the popularity of YouTube videos. With the content and temporal features of the YouTube videos dataset, we use a novel stack of deep learning layers. We validate the approach with state-of-the-art methods and prove that the proposed complex stacked architecture gives more accurate and stable results. Results are also tested for short duration prediction with a different number of reference days after video publishing.
The potentials of partial least squares structural equation modeling (PLS-SEM) in leisure research

Abstract Partial least squares structural equation modeling (PLS-SEM) is a multivariate statistical technique that helps examine complex relationships among a number of variables. Although its use has increased over decades, PLS-SEM remains underutilized in leisure research. The purpose of this methodological paper is to offer a primer on PLS-SEM for leisure researchers and to present a critical review of PLS-SEM’s strengths and limitations, while identifying potential applications of PLS-SEM across different sub-fields and theories in leisure research. Specifically, as to strengths, we discuss PLS-SEM’s sample size requirements, accommodation of formative and reflective measures, ability to model many variables and relationships, and statistical prediction capacity. In terms of its limitations, we review criticisms regarding PLS-SEM’s biased estimates as well as the lack of measurement error estimation and model fit assessment tools. Lastly, we provide recommendations for leisure researchers who wish to use PLS-SEM and journal editors and reviewers who assess PLS-SEM articles.
Assessment of Artificial Intelligence Strategies to Estimate the Strength of Geopolymer Composites and Influence of Input Parameters

Geopolymers might be the superlative alternative to conventional cement because it is produced from aluminosilicate-rich waste sources to eliminate the issues associated with its manufacture and use. Geopolymer composites (GPCs) are gaining popularity, and their research is expanding. However, casting, curing, and testing specimens requires significant effort, price, and time. For research to be efficient, it is essential to apply novel approaches to the said objective. In this study, compressive strength (CS) of GPCs was anticipated using machine learning (ML) approaches, i.e., one single method (support vector machine (SVM)) and two ensembled algorithms (gradient boosting (GB) and extreme gradient boosting (XGB)). All models’ validity and comparability were tested using the coefficient of determination (R2), statistical tests, and k-fold analysis. In addition, a model-independent post hoc approach known as SHapley Additive exPlanations (SHAP) was employed to investigate the impact of input factors on the CS of GPCs. In predicting the CS of GPCs, it was observed that ensembled ML strategies performed better than the single ML technique. The R2 for the SVM, GB, and XGB models were 0.98, 0.97, and 0.93, respectively. The lowered error values of the models, including mean absolute and root mean square errors, further verified the enhanced precision of the ensembled ML approaches. The SHAP analysis revealed a stronger positive correlation between GGBS and GPC′s CS. The effects of NaOH molarity, NaOH, and Na2SiO3 were also observed as more positive. Fly ash and gravel size: 10/20 mm have both beneficial and negative impacts on the GPC′s CS. Raising the concentration of these ingredients enhances the CS, whereas increasing the concentration of GPC reduces it. Gravel size: 4/10 mm has less favorable and more negative effects. ML techniques will benefit the construction sector by offering rapid and cost-efficient solutions for assessing material characteristics.
Understanding the Value of Enterprise Resource Planning (ERP) Systems

Aim/Purpose: The purpose of this research is to explain how ERP systems provide value to companies in Lesotho, a developing country. Background: The percentage of organizations with Enterprise Resource Planning systems (ERPs) has been increasing in both developed and developing nations. Despite the popularity of ERPs, the literature has shown that ERP failure is a major challenge facing organizations. Companies invest a considerable amount of money into these systems, expecting a return on in-vestment. Yet, findings on the benefits that organizations accrue from the implementation of ERPs are mixed. There are concerns that in developing countries the return is low. Methodology: An online survey strategy was used for collecting data from companies. Using the simple random method, 169 companies using ERP systems were selected. Contribution: The core contribution is in supporting proposed relationships that had not been tested prior. The empirical results of this study describe the Lesotho ERP context. The results also emphasize the importance of the use of ERP in determining the value of ERPs. Findings: This study has confirmed that ERP usage and business processes improvements are the main factors affecting ERP value, and ERP usage is the strongest determiner of ERP value. The finding also emphasizes the importance of organizational culture and training. Recommendations for Practitioners: Companies are encouraged to focus on training users and build a supportive organizational culture. Recommendations for Researchers: Context plays a vital role in determining ERP value and hence should be taken into account when explaining ERP value. Impact on Society: The paper highlights the impact of organizational culture on ERP usage and business process improvement and hence ERP value. Future Research: While this study focused on training quality, further studies could focus on the impact of training quantity and ongoing training.
The Influence of IT Capability on Operational Performance Through Internal and External Integration: Evidence from Indonesia

During the Pandemic of COVID-19, many manufacturing companies around the world, such as Indonesia, experienced supply and demand disruption. The PMI index reflecting the operational performance declined to 27.5 in April 2020 from 45 in January 2020. This study investigates the influence of IT capability on operational performance through internal and external integration. The sample consists of 111 manufacturing companies, and data analysis adopts the Partial Least Square (PLS) approach with SmartPLS. The results revealed that nine hypotheses proposed were supported. First, IT capability directly affects internal, external integration, and operational performance. Second, internal and external integration affects operational performance. Third, IT capability indirectly affects operational performance through internal and external integration. This research paves a way on how to recover the operational performance during the pandemic. These findings also contribute to enriching and extending the acceptance of previous research in the manufacturing industry context.
Non-HLA Gene Polymorphisms in the Pathogenesis of Type 1 Diabetes: Phase and Endotype Specific Effects

The non-HLA loci conferring susceptibility to type 1 diabetes determine approximately half of the genetic disease risk, and several of them have been shown to affect immune-cell or pancreatic β-cell functions. A number of these loci have shown associations with the appearance of autoantibodies or with progression from seroconversion to clinical type 1 diabetes. In the current study, we have re-analyzed 21 of our loci with prior association evidence using an expanded DIPP follow-up cohort of 976 autoantibody positive cases and 1,910 matched controls. Survival analysis using Cox regression was applied for time periods from birth to seroconversion and from seroconversion to type 1 diabetes. The appearance of autoantibodies was also analyzed in endotypes, which are defined by the first appearing autoantibody, either IAA or GADA. Analyzing the time period from birth to seroconversion, we were able to replicate our previous association findings at PTPN22, INS, and NRP1. Novel findings included associations with ERBB3, UBASH3A, PTPN2, and FUT2. In the time period from seroconversion to clinical type 1 diabetes, prior associations with PTPN2, CD226, and PTPN22 were replicated, and a novel association with STAT4 was observed. Analyzing the appearance of autoantibodies in endotypes, the PTPN22 association was specific for IAA-first. In the progression phase, STAT4 was specific for IAA-first and ERBB3 to GADA-first. In conclusion, our results further the knowledge of the function of non-HLA risk polymorphisms in detailing endotype specificity and timing of disease development.
Mixed leaf meal supplemented with exogenous enzyme and limiting amino acids can completely replace DORB (de-oiled rice bran) in the diet of Labeo rohita

Various single leaf meal can substitute costly de-oiled rice bran (DORB) in farm made feed for carps. However, the use of mixed leaf meal (LM) in fish feed is not reported yet. Therefore, Vigna mungo, Ipomoea aquatica and Hygrophila spinosa leaf meals were blended in an equal proportion to prepare LM. DORB was the major energy source in control diet (C) and LM substituted 50% and 100% of DORB in LM20 and LM40 experimental diets, respectively. In addition, control diet (C), LM20 and LM40 diets were supplemented with limiting amino acids and exogenous carbohydrases and denoted as CE, LM20E and LM40E, respectively. Labeo rohita fingerlings were fed till satiation for 60 days. Fish fed with LM20E diet exhibited maximum growth rates and feed conversion (p <0.05) however these were similar in C and LM40 (p > 0.05). Amylase and aminotransferase activities were positively related with growth indices (p < 0.05). Difference in hematological indices was negligible (except total leukocyte count), and lactate dehydrogenase activities in DORB and LM-based fed groups (p > 0.05) while lower superoxide dismutase activities was observed in LM fed groups (p < 0.05). The present study concluded that LM up to 400 g kg–1 could be incorporated as complete DORB replacer in L. rohita diet, however, 200 g kg–1 LM supplemented with 0.98 g L-lysine kg–1 and 1 g exogenous enzyme kg–1 registered the best growth, nutrient utilization, feed conversion ratio, physio-metabolic responses and hematological status.
A placa Arduino: uma op»c~ao de baixo custo para experi^encias de f¶‡sica assistidas pelo PC (The Arduino board: a low cost option for physics experiments assisted by PC)

Recebido em 18/4/2010; Aceito em 19/1/2011; Publicado em 21/3/2011Neste trabalho, apresentamos a placa Arduino como uma op»c~ao de muito baixo custo para a aquisi»c~ao dedados com um PC. Duas aplica»c~oes simples que mostram as potencialidades desta placa s~ao brevemente discu-tidos.Palavras-chave: placa Arduino, aquisi»c~ao de dados, oscila»c~oes amortecidas, transfer^encias radiativas.We present the Arduino board as a very low cost option for data acquisition with a PC. Two simple appli-cations that demonstrate the potential of this board are brie°y discussed.Keywords: Arduino board, data acquisition, damped oscillations, radiative transfer.
Essays on the Creation and Development of Organizations

This dissertation adopts a stage perspective and seeks to expand our knowledge on the creation and development of organizations. The three studies presented in this dissertation analyze the impact of individual and environmental factors on activities and processes, as well as outcomes that are characteristic of different developmental stages in an organization’s life cycle. The study presented in Chapter 2 addresses how and under what conditions an organizational-level institutional logic drives researchers’ entrepreneurial intentions. The study presented in Chapter 3 examines, how incubator characteristics impact the development of ventures hosted in incubator facilities. The study underlying the last chapter of this dissertation, Chapter 4, addresses, how top management team characteristics help to explain whether organizations seize the learning opportunities inherent in their failures to improve subsequent performance.
UAV Icing: Experimental Investigation of Ice Shedding Times with an Electrothermal De-Icing System

Icing encounters can reduce the aerodynamic performance of aircraft significantly. To protect aircraft against the adverse effects of icing, ice protection systems are required. As of today, no mature ice protection systems exist for medium-sized fixed-wing unmanned aerial vehicles (UAVs). An important factor for the development of a de-icing system is to determine the required heat loads and heating periods. This work presents ice shedding times from experimental tests in an icing wind tunnel. An RG-15 airfoil equipped with a de-icing system is tested under conditions that are typical for medium-sized drones and cover the three icing regimes of glaze, mixed, and rime ice. The experiments show that increasing the ice protection system's heat flux reduces the time required for the ice to shed. However, the energy efficiency of the de-icing system decreases for higher heat fluxes. Another finding is that the angle of attack influences the shedding times significantly. While the effect of intercycle times on the shedding time depends on the temperature, the system becomes more energy-efficient for longer intercycle times for all temperatures. These results help to define more energy-efficient operation procedures for ice protection systems for UAVs.
A Comparative Feasibility Study for Transcranial Extracorporeal Shock Wave Therapy

The potential beneficial regenerative and stimulatory extracorporeal shock wave therapy (ESWT) applications to the central nervous system have garnered interest in recent years. Treatment zones for these indications are acoustically shielded by bones, which heavily impact generated sound fields. We present the results of high-resolution tissue-realistic simulations, comparing the viability of different ESWT applicators in their use for transcranial applications. The performances of electrohydraulic, electromagnetic, and piezoelectric transducers for key reflector geometries are compared. Based on density information obtained from CT imaging of the head, we utilized the non-linear wave propagation toolset Matlab k-Wave to obtain spatial therapeutic sound field geometries and waveforms. In order to understand the reliability of results on the appropriate modeling of the skull, three different bone attenuation models were compared. We find that all currently clinically ESWT applicator technologies show significant retention of peak pressures and energies past the bone barrier. Electromagnetic transducers maintain a significantly higher energy flux density compared to other technologies while low focusing strength piezoelectric applicators have the weakest transmissions. Attenuation estimates provide insights into sound field degradation and energy losses, indicating that effective transcranial therapies can readily be attained with current applicators. Furthermore, the presented approach will allow for future targeted in silico development and the design of applicators and therapy plans to ultimately improve therapeutic outcomes.
Hydraulic Jump on a Partially Vegetated Bed

Hydraulic jump may form when a supercritical flow runs over a vegetated bottom and change the downstream flow hydraulics and fluid properties after air‐water mixing and energy dissipation at the flow transition. Unlike the abundant literature on hydraulic jump characteristics on engineered or natural sediment rough beds, few studies of vegetation roughness effects have been reported. New experiments were conducted by creating hydraulic jumps with identical inflow Froude numbers on a smooth bed, fully and partly grated rough beds, and partially vegetated grate‐rough beds covered with artificial plants of different densities. The free‐surface dynamics and air‐water flow properties were investigated with primary focus on the interaction between the flow and flexible vegetation barrier/roughness, in addition to the effects of Froude number and inflow roughness conditions. The characteristic jump and jump roller lengths were found shortened as the jump roller was deflected over the vegetation layer. The flow structure modification was observed with a steepening of the roller free‐surface profile and enhanced surface wave propagation, especially when the flow experienced an invert roughness discontinuity at the toe. An increasing bubble detection frequency was obtained in nonvegetated channels when the bed was roughened, but additional vegetation on the rough invert caused reduction in the bubble frequency and cross‐sectional mean air concentration by inducing roller deflection and air bubble detrainment. The results indicated that the effects of perturbing artificial flexible vegetation with relatively large plant height could be different from uniformly distributed rigid bed roughness elements and complicated by the time‐varying flow‐vegetation interaction.