Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Whole or Ground Flaxseed Supplementation on Fatty Acid Profile, Fermentation, and Bacterial Composition in Rumen of Dairy Cows

Flaxseed is rich in α-linolenic acid (ALA) and can increase omega-3 polyunsaturated fatty acid in the milk of dairy cows. However, the response of rumen fermentation to different forms of flaxseed supplementation is unknown. This study aimed to investigate the effect of different forms of flaxseed on the fatty acid profile, fermentation, and composition of bacteria in the rumen of dairy cows. In total, 30 Holstein dairy cows were selected and randomly assigned into three groups (10/group). Cows were fed a basal diet (control check; CK) or basal diets supplemented with either 1,500 g per day whole flaxseed (WF) or 1,500 g per day ground flaxseed (GF). The WF group had the highest ALA content in rumen fluid, whereas no difference was found between the CK and GF groups. However, the molar proportion of acetate increased in the WF and GF groups and was the highest in the GF group, and a similar trend was shown by propionate, isobutyrate, butyrate, isovalerate, and valerate (CK < WF < GF). The abundance of Ruminococcaceae_NK4A214_group, Christensenellaceae_R-7_group, and Eubacterium_coprostanoligenes_group also showed the same trend (CK < WF < GF). Different forms of flaxseed release ALA by different mechanisms in the rumen, and the molar proportions of volatile fatty acids and the bacterial composition were potentially influenced mainly by the amount of ALA released into the rumen.
The Biomechanical Mechanism of Upper Airway Collapse in OSAHS Patients Using Clinical Monitoring Data during Natural Sleep

Obstructive sleep apnea hypopnea syndrome (OSAHS) is a common sleep disorder characterized by repeated pharyngeal collapse with partial or complete obstruction of the upper airway. This study investigates the biomechanics of upper airway collapse of OSASH patients during natural sleep. Computerized tomography (CT) scans and data obtained from a device installed on OSASH patients, which is comprised of micro pressure sensors and temperature sensors, are used to develop a pseudo three-dimensional (3D) finite element (FE) model of the upper airway. With consideration of the gravity effect on the soft palate while patients are in a supine position, a fluid–solid coupling analysis is performed using the FE model for the two respiratory modes, eupnea and apnea. The results of this study show that the FE simulations can provide a satisfactory representation of a patient’s actual respiratory physiological processes during natural sleep. The one-way valve effect of the soft palate is one of the important mechanical factors causing upper airway collapse. The monitoring data and FE simulation results obtained in this study provide a comprehensive understanding of the occurrence of OSAHS and a theoretical basis for the individualized treatment of patients. The study demonstrates that biomechanical simulation is a powerful supplementation to clinical monitoring and evaluation.
Finite-Element Analysis of Magnetically Saturated D-C Machines

The magnetic field distribution in saturated iron parts of electric machines is defined by a nonlinear quasi-Poisson equation. Solution of this equation is equivalent to minimization of a nonlinear energy functional. A recent paper has proposed approximate minimization by means of a finite element method, using triangular finite elements and a quadratically convergent iteration scheme. This new method is now applied to a 5 KW d-c machine, whose no-load and on-load characteristics are predicted and compared with experimental measurements. Good agreement is obtained. Since the pole axis is not an axis of magnetic symmetry under load, a periodicity condition is introduced to relate all magnetic vector potentials to those one pole pitch away. This condition is enforced by means of a special connection matrix, whose derivation is shown in the paper. An automatic plotting program has been developed for graphical plotting of the flux distributions, and several field plots for the machine are shown.
Pharmacogenomics and Personalized Medicine in Type 2 Diabetes Mellitus: Potential Implications for Clinical Practice

Abstract Type 2 diabetes mellitus (T2DM) is the most common form of diabetes, and is rising in incidence with widespread prevalence. Multiple gene variants are associated with glucose homeostasis, complex T2DM pathogenesis, and its complications. Exploring more effective therapeutic strategies for patients with diabetes is crucial. Pharmacogenomics has made precision medicine possible by allowing for individualized drug therapy based on a patient’s genetic and genomic information. T2DM is treated with various classes of oral hypoglycemic agents, such as biguanides, sulfonylureas, thiazolidinediones, meglitinides, DPP4 inhibitors, SGLT2 inhibitors, α-glucosidase inhibitors, and GLP1 analogues, which exhibit various pharmacogenetic variants. Although genomic interventions in monogenic diabetes have been implemented in clinical practice, they are still in the early stages for complex polygenic disorders, such as T2DM. Precision DM medicine has the potential to be effective in personalized therapy for those suffering from various forms of DM, such as T2DM. With recent developments in genetic techniques, the application of candidate-gene studies, large-scale genotyping investigations, genome-wide association studies, and “multiomics” studies has begun to produce results that may lead to changes in clinical practice. Enhanced knowledge of the genetic architecture of T2DM presents a bigger translational potential. This review summarizes the genetics and pathophysiology of T2DM, candidate-gene approaches, genome-wide association studies, personalized medicine, clinical relevance of pharmacogenetic variants associated with oral hypoglycemic agents, and paths toward personalized diabetology.
Simulation einer sensorgestützten Präzisionsbewässerung von Standorten im Südtiroler Obstanbau

Kurzfassung : Die Folgen des Klimawandels machen einen bewussteren Umgang mit den Wasserressourcen notwendig. Insbesondere in Agrarregionen, welche nur unter hohem Bewasserungseinsatz wirtschaftlich rentable Ertrage liefern, kann durch eine bedarfsorientierte und teilflachenspezifische Bewasserung eine bedeutende Wassereinsparung ohne Ertragseinbusen erreicht werden. Mehrjahrige bodenhydrologische Untersuchungen in den bewasserten Obstanbauregionen Sudtirols haben ergeben, dass die pedologischen Standortunterschiede einen bedeutenden, bisher aber meist unbeachteten, Einfluss auf die lokalen Variationen der Bodenwasserdynamik und der fur diePflanzen verfugbare Wassermenge haben. Numerische und agenten-basierte Simulationsversuche haben gezeigt, dass eine dynamisch gesteuerte Bewasserung durch den Einsatz bodenspezifisch kalibrierter Feuchtesensoren eine optimierte Wasserzufuhr ermoglicht. Durch eine verkurzte Bewasserungsdauer mit variablen Intensitaten, welche sich an bodenphysikalischen Kennwerten orientieren, konnen deutliche Wassereinsparungen erzielt werden. Einer geplanten Validierung an Bodensaulen im Labor und Optimierung dieses Simulationsansatzes soll eine Praxisprufung im Freigelande folgen. Abstract: In many climatic regions, the availability of water in soils determines to a large extent their agricultural productiveness. Especially in irrigated agricultural areas information about the actual soil water dynamics can deliver valuable data to optimize the irrigation practice with regard to volume and duration of irrigation. South Tyrol is a region where these questions are discussed currently. Intensive orcharding is practised there within an area of about 18.000 hectares. Because of the local climatic situation irrigation is considered necessary and hasbeen practised for a long time. However, at many locations much more water is used for irrigation than the apple trees actually need. Regarding the aspects of climatic change and the decrease of water resources, the term “precision irrigation” is being increasingly discussed. Such a precision irrigation must be based on objective and quantitative criteria, which focus primarily on the physical soil properties and hydrologic balances. One solution would be to have sensors near the plants’ roots controlling the water inflow depending on the particular demand. Such a dense soil-hydrological measuring network should be composed ideally of micro-sensors, which are distributed in the investigated soil section and thereby collect data of relevant parameters in the pedosphere usinghigh temporal resolution and transmitting the information to a central logger-unit. This contribution will present a simulation-based approach of a precision irrigation-system with particular consideration of pedo-specific properties.
The Prebiotic Kitchen: A Guide to Composing Prebiotic Soup Recipes to Test Origins of Life Hypotheses

“Prebiotic soup” often features in discussions of origins of life research, both as a theoretical concept when discussing abiological pathways to modern biochemical building blocks and, more recently, as a feedstock in prebiotic chemistry experiments focused on discovering emergent, systems-level processes such as polymerization, encapsulation, and evolution. However, until now, little systematic analysis has gone into the design of well-justified prebiotic mixtures, which are needed to facilitate experimental replicability and comparison among researchers. This paper explores principles that should be considered in choosing chemical mixtures for prebiotic chemistry experiments by reviewing the natural environmental conditions that might have created such mixtures and then suggests reasonable guidelines for designing recipes. We discuss both “assembled” mixtures, which are made by mixing reagent grade chemicals, and “synthesized” mixtures, which are generated directly from diversity-generating primary prebiotic syntheses. We discuss different practical concerns including how to navigate the tremendous uncertainty in the chemistry of the early Earth and how to balance the desire for using prebiotically realistic mixtures with experimental tractability and replicability. Examples of two assembled mixtures, one based on materials likely delivered by carbonaceous meteorites and one based on spark discharge synthesis, are presented to illustrate these challenges. We explore alternative procedures for making synthesized mixtures using recursive chemical reaction systems whose outputs attempt to mimic atmospheric and geochemical synthesis. Other experimental conditions such as pH and ionic strength are also considered. We argue that developing a handful of standardized prebiotic recipes may facilitate coordination among researchers and enable the identification of the most promising mechanisms by which complex prebiotic mixtures were “tamed” during the origin of life to give rise to key living processes such as self-propagation, information processing, and adaptive evolution. We end by advocating for the development of a public prebiotic chemistry database containing experimental methods (including soup recipes), results, and analytical pipelines for analyzing complex prebiotic mixtures.
Understanding and improving automated collaborative filtering systems

Automated collaborative filtering (ACF) is a software technology that provides personalized recommendation and filtering independent of the type of content. In an ACF system, users indicate their preferences by rating their level of interest in items that the system presents. The ACF system uses the ratings information to match together users with similar interests. Finally, the ACF system can predict a user's rating for an unseen item by examining his neighbors' ratings for that item. This dissertation presents a set of results with the goal of improving the effectiveness and understanding of ACF systems. The results cover four challenges: understanding and standardizing evaluation of ACF systems, improving the accuracy of ACF systems, designing and utilizing effective explanations for ACF predictions, and improving ACF to support ephemeral recommendations. To address these challenges, a combination of offline analysis and user testing is used. All of the evaluation metrics that have been proposed for ACF are examined theoretically and compared empirically. The empirical results show that all proposed ACF evaluation metrics perform similarly, which argues for the adoption of a standardized evaluation metric—for which I propose mean absolute error. With respect to improving algorithm accuracy, I present a detailed empirical examination of the neighborhood-based prediction algorithm, which has been the most successful algorithm, both in research and in commercial applications. ACF systems predict based on data of variable quantity and quality, but current ACF systems are black boxes, so users have no indication of when to trust an ACF prediction. Explanations expose some of the process and data behind the ACF prediction, allowing users to judge if a prediction is appropriate for their current context of risk. I present results showing what forms of explanation users find the most compelling, as well as indications that explanations can increase the acceptance of ACF systems. Finally, I present results from tests of a new algorithm for supporting focused ephemeral user information needs. Ephemeral information needs are those needs that are immediate, focused, and often temporary. The proposed algorithm provides support for ephemeral information needs using no additional data beyond the standard ACF ratings.
Neural networks for process monitoring, control and fault detection: Application to Tennessee Eastman Plant

This paper discusses the application of artificial neural networks in the area of process monitoring, process control and fault detection. Since chemical process plants are getting more complex and complicated, the need of schemes that can improve process operations is highly demanded. Artificial neural network can provide a generic, non-linear solution, and dynamic relationship between cause and effect variables for complex and non-linear processes. This paper will describe the application of neural network for monitoring reactor temperature, estimation and inferential control of a fatty acid composition in a palm oil fractionation process and detection of reactor sensor failures in the Tennessee Eastman Plant (TEP). The potential for the application of neural network technology in the process industries is great. Its ability to capture and model process dynamics and severe process non-linearities makes it powerful tools for process monitoring, control and fault detection.
List Models of Procedure Learning

This paper presents a new theory of the initial stages of skill acquisition and then employs the theory to model current and future training programs for fight management systems (FMSs) in modern commercial airliners like the Boeing 777 and the Airbus A320. The theoretical foundations for the theory are a new synthesis of the literature on human memory and the latest version of the ACT-R theory of skill acquisition.
Comparative finite element analysis of synchronous reluctance machines with internal rotor flux barriers

Synchronous reluctance machines with internal rotor flux barriers can be designed to have a high saliency. Permanent magnets inserted into the rotor flux barriers considerably increase the effective saliency. In comparison with the conventional synchronous reluctance machine, this permanent magnet assisted synchronous reluctance machine offers better torque capacity and power factors. A nonlinear finite element analysis is used to evaluate the parameters of a 5 kW machine with a field-weakening range of 5.33:1. The characteristics of both the conventional reluctance machine and the permanent magnet assisted reluctance machine are compared. The investigation of the complex stator inductance shows the high suitability of the concerned machine for an application in position-sensorless drives.
Closed-Loop Supply Chains : New Developments to Improve the Sustainability of Business Practices

A Commentary on Closed Loop Supply Chains Mark Ferguson and Gilvan Souza STRATEGIC CONSIDERATIONS Strategic Issues in Closed Loop Supply Chains with Remanufacturing Mark Ferguson Environmental Legislation Regarding Product Take-back and Recovery Atalay Atasu and Luk van Wassenhove Product Design Issues Bert Bras TACTICAL CONSIDERATIONS Designing the Reverse Logistics Network Necati Aras, Tamer Boyaci, and Vedat Verter Product Acquisition, Grading, and Disposition Decisions Moritz Fleischmann, Michael Galbreth, and George Tagaras Production Planning in Remanufacturing Gilvan Souza Analyzing the Market for Remanufactured Products Ravi Subramanian INDUSTRY CHARACTERISTICS AND CASE STUDIES Examples of Existing Profitable Practices in Product Take-back and Recovery Mark Ferguson, Gilvan Souza, and Beril Toktay Reuse and Recycling in the Movie Industry Charles Corbett Reverse Supply Chain in Hospitals: Lessons from Three Case Studies in Montreal Rajesh Tyagi, Stephan Vachon, Sylvain Landry, and Martin Beaulieu INTERDISCIPLINARY RESEARCH ON CLOSED LOOP SUPPLY CHAINS Interdisciplinarity in Closed-Loop Supply Chain Management Research Vishal Agrawal and Beril Toktay Empirical Studies in Closed-loop Supply Chains: Can We Build a Greener Mousetrap? Stephan Vachon and Robert Klassen Conclusion and Future Research Directions Mark Ferguson and Gilvan Souza
Guidance for a large tabletop exercise for a nuclear power plant

Tabletop exercises are held to discuss issues related to the response of organizations to an emergency event. This document describes in task format the planning, conduct, and reporting of lessons learned for a large interagency tabletop. A sample scenario, focus areas, and discussion questions based on a simulated accident at a commercial nuclear power plant are provided.
Experimental and empirical evaluation of strength for sustainable lightweight self-compacting concrete by recycling high volume of industrial waste materials

Abstract This work aims to study the relationship between the results of lightweight self compacting concrete (LWSCC) made with waste expanded polystyrene (EPS) beads to find an empirical equation to predict mechanical characteristics and compare their results with code empirical equations. The workability and hardened characteristics were examined for sustainable LWSCC which was produced with a water to binder ratio of 0.35 and substituted the normal coarse aggregate with different volume fractions of EPS beads at 0%, 40%, 50%, 60%, 70%, and 80%. All the mixes contain a binder content of 500 kg/m3. Slump flow diameter and time, as well as V-shape flow time, were used to determine the workability of LWSCCs. Additionally, hardened properties such as dry density, ultrasonic pulse velocity (UPV), water absorption, compressive, flexural, and splitting tensile strengths are evaluated. The results confirmed that increasing the amount of EPS increased the workability of LWSCCs while decreasing the strength value, but the compressive strength met the lower limit specified by ACI for structural applications. Additionally, there was a strong linear correlation between the mechanical results. The actual strengths compared with the empirical models presented in codes and literature studies found that the actual results are closest to ACI 363.
End-user Preference for and Understanding of Hurricane Forecast Graphs

Hurricane forecast graphics have the challenging task of communicating information about spatio-temporal uncertainty. This study assesses the impact of graph literacy and graph format on user preference and understanding. In a laboratory setting, we compared user responses to official National Hurricane Center advisory maps and alternative visualizations. Results indicate that prior experience with a visualization drives preference and that graph literacy, visualization format, and tropical cyclone characteristics, in combination, influence interpretations of hurricane forecast track. The findings from this study are expected to inform redesign efforts of hurricane risk communication products.
Steroid-resistant nephrotic syndrome associated MYO1E mutations have differential effects on myosin 1e localization, dynamics, and activity

Myo1e is a non-muscle motor protein enriched in the podocyte foot processes. Mutations in MYO1E are associated with steroid-resistant nephrotic syndrome (SRNS). Here, we set out to differentiate between the pathogenic and neutral MYO1E variants identified in SRNS patients by exome sequencing. Based on protein sequence conservation and structural predictions, two mutations in the motor domain, T119I and D388H, were selected for this study. EGFP-tagged Myo1e constructs were delivered into the Myo1e-KO podocytes via adenoviral infection to analyze Myo1e protein stability, Myo1e localization, and clathrin-dependent endocytosis, which is known to involve Myo1e activity. Furthermore, truncated Myo1e constructs were expressed using the baculoviral expression system and used to measure Myo1e ATPase and motor activity in vitro. Both mutants were expressed as full-length proteins in the Myo1e-KO podocytes. However, unlike wild-type (WT) Myo1e, the T119I variant was not enriched at the cell junctions or clathrin-coated vesicles (CCVs) in podocytes. In contrast, the D388H variant localization was similar to the WT. Surprisingly, the dissociation of the D388H variant from cell-cell junctions and CCVs was decreased, suggesting that this mutation also affects Myo1e activity. The ATPase activity and the ability to translocate actin filaments were drastically reduced for the D388H mutant, supporting the findings from cell-based experiments. The experimental pipeline developed in this study allowed us to determine that the T119I and D388H mutations appear to be pathogenic and gain additional knowledge in the Myo1e role in podocytes. This workflow can be applied to the future characterization of novel MYO1E variants associated with SRNS.
Learning from experience in sustainability

This paper explores the apparent contradiction between the 'linearity' of most Sustainability Indicator (SI) projects, with defined outputs achieved in a set period of time, and an implied 'circularity' that goes with most sustainable development (SD) initiatives. Projects usually have clear parameters within which they are implemented, and the inclusion of elements such as the need for accountability, measurable impact and 'value for money' have grown in importance. Whether we like it or not, it could be argued that we live in a 'projectified' world. We suggest that one way of exploring this potential contradiction between 'linearity' and 'circularity' is to frame the project with a Kolb Learning Cycle heuristic. This will facilitate a rationalisation from those implementing the SI project as to why decisions are being made and for whom. If these questions are opened up to the project stakeholders, including beneficiaries, then the Kolb cycle could encourage learning and understanding by all involved. It is suggested that such learning should be a valid output of the SI project, although typically the focus is only upon the final list of SIs and how they feed into policy. Funders need to take a broader perspective by allowing for both within SI projects, even if learning is not a measurable or tangible outcome. These points are explored within the context of the wider literature and SI projects in Malta and Lebanon.