Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy of Fecal Microbiota Transplantation in Irritable Bowel Syndrome: A Meta-Analysis of Randomized Controlled Trials

Background Randomized controlled trials (RCTs) have examined the efficacy of fecal microbiota transplantation (FMT) in irritable bowel syndrome (IBS) with inconsistent results. We performed a meta-analysis to assess both the short- and long-term efficacy of FMT in IBS. Methods MEDLINE, EMBASE, and the Cochrane Central Register were searched through September 2021. RCTs recruiting adult patients with IBS that compared FMT with placebo with dichotomous data of response to therapy were eligible. Dichotomous data were pooled to obtain a relative risk (RR) of symptom not improving after therapy. RR was also pooled for adverse events (AEs). Continuous data were calculated using a mean difference for IBS-Quality of Life (IBS-QoL). GRADE methodology was used to assess quality of evidence. Results The search strategy generated 658 citations. Seven RCTs comprising 472 patients with IBS were included. FMT was not associated with a significant improvement in global symptom in IBS at 12 weeks in comparison with placebo (RR 0.75, 95% CI 0.43–1.31) with high heterogeneity between studies (I2 87%). Subgroup analyses showed that FMT was superior to placebo when administered via colonoscopy or gastroscope (RR 0.70, 95% CI 0.51–0.96; RR 0.37, 95% CI 0.14–0.99, respectively, while FMT was inferior to placebo when administered via oral capsules (RR 1.88, 95% CI 1.06–3.35). FMT induced a significant improvement in IBS-QoL compared to placebo (mean difference 9.39, 95% CI 3.86–14.91) at 12 weeks. No significant difference in the total number of AEs was observed between FMT and placebo (RR 1.20, 95% CI 0.59–2.47). FMT did not significantly improve global symptom in IBS at 1-year follow-up compared with placebo (RR 0.90, 95% CI 0.72–1.12). The GRADE quality evidence to support recommending FMT in IBS was very low. Conclusion IBS patients may benefit from FMT when administered via colonoscopy or gastroscope. FMT may improve the quality of life of IBS. The long-term use of FMT in IBS warrants further investigation. There is very-low-quality evidence to support recommending FMT in IBS.
Enhancing Sorghum Yield Through Efficient Use of Nitrogen – Challenges and Opportunities

Sorghum is an important crop, which is widely used as food, forage, fodder and biofuel. Despite its natural adaption to resource-poor and stressful environments, increasing yield potential of sorghum under more favorable conditions holds promise. Nitrogen is the most important nutrient for crops, having a dynamic impact on all growth, yield, and grain-quality-determining processes. Thus, increasing nitrogen use efficiency (NUE) in sorghum would provide opportunities to achieve higher yield and better-quality grain. NUE is a complex trait, which is regulated by several genes. Hence, exploring genetic diversity for NUE can help to develop molecular markers associated with NUE, which can be utilized to develop high NUE sorghum genotypes with greater yield potential. Research on improving NUE in sorghum suggests that, under water-deficit conditions, traits such as stay-green and altered canopy architecture, and under favorable conditions, traits such as an optimized stay-green and senescence ratio and efficient N translocation to grain, are potential breeding targets to develop high NUE sorghum genotypes. Hence, under a wide range of environments, sorghum breeding programs will need to reconsider strategies and develop breeding programs based on environment-specific trait(s) for better adaptation and improvement in productivity and grain quality. Unprecedented progress in sensor-based technology and artificial intelligence in high-throughput phenotyping has provided new horizons to explore complex traits in situ, such as NUE. A better understanding of the genetics and molecular pathways involving NUE, accompanied by targeted high-throughput sensor-based indices, is critical for identifying lines or developing management practices to enhance NUE in sorghum.
Targeting Glycolysis in Alloreactive T Cells to Prevent Acute Graft-Versus-Host Disease While Preserving Graft-Versus-Leukemia Effect

Alloreactive donor T cells undergo extensive metabolic reprogramming to become activated and induce graft-versus-host disease (GVHD) upon alloantigen encounter. It is generally thought that glycolysis, which promotes T cell growth and clonal expansion, is employed in this process. However, conflicting data have been reported regarding the requirement of glycolysis to induce T cell-mediated GVHD due to the lack of T cell-specific treatments using glycolysis inhibitors. Importantly, previous studies have not evaluated whether graft-versus-leukemia (GVL) activity is preserved in donor T cells deficient for glycolysis. As a critical component affecting the clinical outcome, it is necessary to assess the anti-tumor activity following treatment with metabolic modulators in preclinical models. In the present study, we utilized T cells selectively deficient for glucose transporter 1 (Glut1T-KO), to examine the role of glycolysis exclusively in alloreactive T cells without off-targeting effects from antigen presenting cells and other cell types that are dependent on glycolysis. We demonstrated that transfer of Glut1T-KO T cells significantly improved acute GVHD outcomes through increased apoptotic rates, impaired expansion, and decreased proinflammatory cytokine production. In addition to impaired GVHD development, donor Glut1T-KO T cells mediated sufficient GVL activity to protect recipients from tumor development. A clinically relevant approach using donor T cells treated with a small molecule inhibitor of glycolysis, 2-Deoxy-D-glucose ex vivo, further demonstrated protection from tumor development. These findings indicate that treatment with glycolysis inhibitors prior to transplantation selectively eliminates alloreactive T cells, but spares non-alloreactive T cells including those that protect against tumor growth. The present study has established a definitive role for glycolysis in acute GVHD and demonstrated that acute GVHD can be selectively prevented through targeting glycolysis.
Studying the Relationship between Erp and The Performance of Lean Production in "Iran Khodro Industrial Group"

What is known as controlling a system is related to the variables of planning properly, an approach toward development, making appropriate decisions within changing conditions, satisfying and maintaining dignity of all stakeholders and achieving an excellent and lean level. Formulating a pure strategy toward detecting and removing the sources of dissipation aims to minimize the costs and make the organization move toward proficiency and organizational excellence. The above definitions are representative of the degree of similarity and existence of a relation between the ERP and Lean Production objectives. The present study aims to introduce these systems, their goals and their potential synergistic. Therefore, the purpose of the research is detecting the impacts of ERP system on lean manufacturing system in IRAN KHODRO Industry Group. The research also had some minor purposes such as detecting those lean manufacturing techniques affected by ERP modules. In this regard, after detecting the lean production tools in company and considering the details of ERP modules in company, we defined the research questions for experts, results were determined using SPSS software and at the end, According to confirming six hypotheses out of 10, the existence of a relation between these two systems was confirmed.
OPTIMAL PERFORMANCE-BASED DESIGN OF STEEL FRAMES USING ADVANCED METAHEURISTICS

In the present paper, seismic performance-based optimization of steel frames is implemented using a number of advanced meta-heuristic algorithms. The optimization process is implemented by two newly developed meta-heuristics, dolphin echolocation optimization (DEO) and enhanced colliding bodies optimization (ECBO). In the present study, a slight modification is achieved on the ECBO to improve its convergence rate and therefore it is named here as ECBO-II. Furthermore, the results of DEO, ECBO and ECBO-II are compared with those of particle swarm optimization (PSO). Evaluating the structural responses by nonlinear time-history analysis during the optimization process is very time consuming. In order to reduce the computational rigor, radial basis function (RBF) neural network is utilized to predict the necessary structural time-history responses during the optimization process. Two numerical examples are presented to illustrate the efficiency of the meta-heuristics for tackling the seismic performance-based optimization problems.
Intelligent Modelling Techniques of Power Load Forecasting for the Western Area of Saudi Arabia@@@النمذجة الذكية والتقنية الأفضل لدراسة التنبؤ بالأحمال في المنطقة الغربية بالمملكة العربية السعودية

Load forecasting has become in recent years one of the major areas of research in electrical engineering. Most traditional forecasting models and artificial intelligence neural network techniques have been tried out in this task. Artificial neural networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This paper presents the development of an ANN-based short-term load forecasting model with improved accuracy for the Regional Power Control Centre of Saudi Electricity Company, Western Operation Area (SEC-WOA). The proposed ANN is trained with weather-related data, special events indexes and historical electric load-related data using the data from the calendar years 2003, to 2007 for training. Different neural networks topologies have been trained and tested for achieve the optimal topology and ranking the input variables in terms of their importance. Based on the optimal NN topology, the network has been trained to predict the ahead load at different time intervals.
Demonstrating New Possibilities for Playful Collaboration: Claystation [Making Auckland]

Abstract Given the growing specialisation of discipline fields, the complexity of the urban sustainability challenge and the increasing scale of projects, collaboration has become more, not less, important. This paper explores how and in what way participatory events can foster collaboration. It explores the Claystation [making Auckland] event and some of the outcomes from this experimental approach to developing a platform for playful collaboration. This action research project involved the recording of the three-day participatory event through pictures and video along with the collection of reflections from participants and observers. The research demonstrated the potential of the event and signalled ways in which it could be adapted to help deliver collaborative outcomes between allied professionals.
Thermal control of stored grains insects by utilizing solar energy

Storage insect-pests are the major cause of damage and losses in food grain. For prevention of damage and losses by insects infestation, all insects present in the stored product must be eliminated at any stage of their development. Preservation methods which applied to food products for insect pests control, as chemical method, resulted in several problems and hazard for consumers. Heat treatment is one of the safe alternative measures for storage insects control but it is costy and requires special facilities for application. Therefore, the aim of this study is to utilize solar radiation as source of heat for thermal control of storage insects, in an attempt to find out a safer effective control measure at minimal cost. To study the effect of material, black paint, and transparent cover on heat observation, four groups of containers were made from differernt materials (plastic, polythene, metal and jute). Two containers from each group (out of three) were painted black and one from these two black containers was covered with transparent polythene. All containers were filled with equal amounts of sorghum grains and kept out door for exposure to direct sun radiation. Temperature measurements were taken at two hours time interval from 8:00 a.m. to 1:00 p.m. for the first period and from 1:00 p.m. to 5:00 p.m. for the second period.
A HIGH BANDWIDTH AIR BEARING BALANCE FOR DYNAMIC WIND TUNNEL TESTING

This paper describes the development of an air bearing with high bandwidth load sensing capabilities and a means of delivering high pressure air to the rotating (floating) element. The device will be used to provide nearly frictionless rotation to wind tunnel test models while measuring unsteady aerodynamic loads. Although the current application involves dynamic testing of missiles, it will be useful in the study of longitudinal high-alpha aircraft dynamics. The load sensing is based on measurements of pressures in the bearing gas film using micromachined fast response (1 ms) sensors. The air bearing balance also provides a supply of high pressure air to the test model for reaction control jets and pneumatic flow control devices. This paper describes the design and evaluation of a prototype capable of single-axis rotation. Static calibration experiments confirm that the prototype can sense multi-axis loads precisely. Frequency response tests demonstrated the ability to detect unsteady loads at least as high as 200 Hz. Further demonstrations showed that the balance can deliver high pressure air to the test model without friction and without hampering load sensing. The prototype will serve as the basis for an air bearing balance capable of three-axis rotation.
Collaboration of Ultrasonic Irradiation and Silica Nanoparticles in the Diastereoselective Synthesis of Trans-2,3-Dihydrofuran Derivatives: An Exceptional Catalytic Activity of Sound Cavities and SiO2 Nanoparticles

Abstract Coupling ultrasonic irradiation with nanoparticles has the potential to result in the synergistic mild and multi-component synthesis of valuable organic compounds. In this work, a fast and one-step strategy was developed for the diastereoselective synthesis of trans-2,3-dihydrofuran derivatives. The combination of ultrasonic waves and silica nanoparticles was promoted the eco-friendly condensation of aromatic aldehydes, 4-hydroxycoumarin, and phenacyl pyridinium bromide with each other in aqueous media smoothly. The method is fast, has high yields compared to the conventional method, low catalyst loading. The catalyst is inexpensive and very mild also is recyclable in six runs without appreciable loss of activity. This sonochemical assisted methodology is the first report of a green and unique one-pot process for the synthesis of trans-2,3-dihydrofurans over silica nanoparticles as a nonmetal oxide catalyst. Graphical Abstract
The Technological-Pedagogical Knowledge for In-Service Teachers in Primary Education: A Systematic Literature Review

This article presents the results of a scientific literature analysis based on Kitchenham ’ s (2004) proposal, regarding the technological-pedagogical knowledge of the content under the TPACK model. Research studies containing data-driven information in primary education were revised. The selection of the 622 articles was conducted in Scopus, WoS (Web of Science), ERIC (Educational Resources Information Center), and Google Scholar databases; considering the period from which this model was initially described to May 2019. The following criteria were also observed: open access sources, referring to social sciences, and full text available. To conclude, there is limited scientific production regarding TPACK model in primary education, with 3,05% of the articles reviewed in this systematic literature review. An increase in using the TPACK model in terms of teacher knowledge and enriched environments with information and communication technology has also been observed. Participation of other members of the school community as students, parents and managers is also recommended.
A novel approach for the detection of anomalous energy consumption patterns in industrial cyber‐physical systems

Most scenarios emerging from the Industry 4.0 paradigm rely on the concept of cyber‐physical production systems (CPPS), which allow them to synergistically connect physical to digital setups so as to integrate them over all stages of product development. Unfortunately, endowing CPPS with AI‐based functionalities poses its own challenges: although advances in the performance of AI models keep blossoming in the community, their penetration in real‐world industrial solutions has not so far developed at the same pace. Currently, 90% of AI‐based models never reach production due to a manifold of assorted reasons not only related to complexity and performance: decisions issued by AI‐based systems must be explained, understood and trusted by their end users. This study elaborates on a novel tool designed to characterize, in a non‐supervised, human‐understandable fashion, the nominal performance of a factory in terms of production and energy consumption. The traceability and analysis of energy consumption data traces and the monitoring of the factory's production permit to detect anomalies and inefficiencies in the working regime of the overall factory. By virtue of the transparency of the detection process, the proposed approach elicits understandable information about the root cause from the perspective of the production line, process and/or machine that generates the identified inefficiency. This methodology allows for the identification of the machines and/or processes that cause energy inefficiencies in the manufacturing system, and enables significant energy consumption savings by acting on these elements. We assess the performance of our designed method over a real‐world case study from the automotive sector, comparing it to an extensive benchmark comprising state‐of‐the‐art unsupervised and semi‐supervised anomaly detection algorithms, from classical algorithms to modern generative neural counterparts. The superior quantitative results attained by our proposal complements its better interpretability with respect to the rest of algorithms in the comparison, which emphasizes the utmost relevance of considering the available domain knowledge and the target audience when design AI‐based industrial solutions of practical value. Finally, the work described in this paper has been successfully deployed on a large scale in several industrial factories with significant international projection.
The impact of redundancy on resilience engineering in a petrochemical plant by data envelopment analysis

Resilience engineering is a new and proactive attitude toward improving the safety and reliability of complex industrial systems such as oil and gas companies and petrochemical plants. This study aims to evaluate the effect of redundancy on a resilient system and determine which redundancy in different aspects including human resources and equipment items (hardware, software, and information) is more efficient in a resilient system through data envelopment analysis. Data collection was performed in a petrochemical plant through a questionnaire. Then, reliability of the data was calculated through Cronbach’s alpha test. Next, the effects of human redundancy and equipment redundancy on resilience engineering are examined by means of data envelopment analysis approach. The results show that efficiency of the resilient system is improved by considering both equipment redundancy and human redundancy. It is also revealed that human redundancy is more effective in resilient system performance compared to equipment redundancy. Hence, human redundancy plays a vital role in efficiency enhancement of resilient systems. This study is among the first ones that investigate the impact of the redundancy in resilient systems in different aspects including human and equipment redundancy by means of data envelopment analysis approach and highlights the gaps between managers and staff about the impact of equipment redundancy and human redundancy on resilience engineering.
Traditional and Modern Analysis Performance Indicators: Evidence from New York Stock Exchange

Assessment of company performance can be done using traditional and modern techniques. Each test carried out has the advantages and disadvantages of the order if applied to companies listed on major stock exchanges. This study aims to determine the traditional and modern analysis of stock performance indicators on the New York Stock Exchange. The company index used was the Dow Jones index. Company performance was measured using two indicators, namely modern performance indicators reflected in Economic Value Added (EVA) and traditional performance indicators reflected in Return on Assets (ROA), Return on Equity (ROE), Earning Per Share (EPS), and Dividend Per Share (DPS). This research was conducted employing purposive sampling on 29 companies indexed by Dow Jones during the 2015-2018 period. The data analysis techniques used were descriptive statistics, classical assumption test, and multiple regression analysis. The results of hypothesis testing in this study show that partially modern performance indicator, namely Economic Value Added (EVA), has an insignificant and negative effect on Stock Return. Meanwhile, traditional performance indicators, namely Return on Assets (ROA), Return on Equity (ROE), Earning Per Share (EPS), and Dividend Per Share (DPS) have a significant and positive effect on Stock Return. The results of simultaneous hypothesis testing show that Economic Value Added (EVA), Return on Assets (ROA), Return on Equity (ROE), Earning Per Share (EPS), and Dividend Per Share (DPS) have a significant and positive effect on Stock Return.Keywords: Economic Value Added (EVA), Return on Asset (ROA), Return on Equity (ROE), Earning Per Share (EPS), and Dividend Per Share (DPS), Stock Return.
A digital input class-D audio amplifier with sixth-order PWM

A digital input class-D audio amplifier with a sixth-order pulse-width modulation(PWM)modulator is presented.This modulator moves the PWM generator into the closed sigma–delta modulator loop.The noise and distortions generated at the PWM generator module are suppressed by the high gain of the forward loop of the sigma–delta modulator.Therefore,at the output of the modulator,a very clean PWM signal is acquired for driving the power stage of the class-D amplifier.A sixth-order modulator is designed to balance the performance and the system clock speed.Fabricated in standard 0.18 m CMOS technology,this class-D amplifier achieves 110 dB dynamic range,100 dB signal-to-noise rate,and 0.0056%total harmonic distortion plus noise.
A Single-Loop Kriging Surrogate Modeling for Time-Dependent Reliability Analysis

Current surrogate modeling methods for time-dependent reliability analysis implement a double-loop procedure, with the computation of extreme value response in the outer loop and optimization in the inner loop. The computational effort of the double-loop procedure is quite high even though improvements have been made to improve the efficiency of the inner loop. This paper proposes a single-loop Kriging (SILK) surrogate modeling method for time-dependent reliability analysis. The optimization loop used in current methods is completely removed in the proposed method. A single surrogate model is built for the purpose of time-dependent reliability assessment. Training points of random variables and over time are generated at the same level instead of at two separate levels. The surrogate model is refined adaptively based on a learning function modified from timeindependent reliability analysis and a newly developed convergence criterion. Strategies for building the surrogate model are investigated for problems with and without stochastic processes. Results of three numerical examples show that the proposed single-loop procedure significantly increases the efficiency of time-dependent reliability analysis without sacrificing the accuracy. [DOI: 10.1115/1.4033428]