Miracle-dz/UniFAR-FTUs huggingface dataset:
Edinburgh Explorer Rotary Adsorption: Selective Recycling of CO2 in Combined Cycle Gas Turbine Power Plants

A conceptual design assessment shows that the use of structured adsorbents in a regenerative adsorption wheel is technically feasible for the application of selective exhaust gas recirculation (SEGR) in combined cycle gas turbine (CCGT) power plants. As the adsorber rotates, CO 2 is selectively transferred from a ﬂ ue gas stream to an ambient air stream fed to the gas turbine compressor, increasing the CO 2 concentration and reducing the ﬂ ow rate of the fraction of the ﬂ ue gases treated in a post-combustion CO 2 capture system. It imposes an estimated pressure drop of 0.25 kPa, unlike a pressure drop of 10 kPa reported for selective CO 2 membrane systems, preventing a signi ﬁ cant derating of the gas turbine. An equilibrium model of a rotary adsorber with commercially available activated carbon evaluates the inventory of the adsorbent and sizes the wheel rotor. Two rotary wheels of 24 m diameter and 2 m length are required per gas turbine — heat recovery steam generator train to achieve an overall CO 2 capture level of 90% in a CCGT power plant (ca. 820 MW e ) with SEGR “ in parallel ” to the capture plant. Two to ﬁ ve rotary wheels are required for a con ﬁ guration with SEGR “ in series ” to the capture plant. A reduction of 50% in the mass of the adsorbent would be possible with Zeolite 13X instead of activated carbon, yet the hydrophilicity of zeolites are detrimental to the capacity and upstream dehydration of the ﬂ ue gases is required. A parametric analysis of the equilibrium properties provides guidelines for adsorbent development. It suggests the importance of balancing the af ﬁ nity for CO 2 to allow the regeneration of the adsorbent with air at near ambient pressure and temperature, to minimise the inventory of the adsorbent within practical limits. An adsorbent with a saturation capacity of 8 mol/kg, a heat of adsorption from 24 to 28 kJ/mol CO 2 and a pre-exponential factor of the equilibrium constant from 2 × 10 – 6 to 9 × 10 – 6 kPa − 1 would result in an inventory below 200 kg, i.e., approximately the limit for the use of a single rotary wheel system.
The Politics of Progressivity: Court-Ordered Reforms, Racial Difference, and School Finance Fairness

This article contributes to our understanding of American education politics by exploring when and why states redistribute K–12 education dollars to poorer schools. It does so by examining three explanations for intrastate changes in progressivity: court-ordered finance reforms, political trends, and demographic changes. Using state-level data from 1995 to 2016, we find mixed evidence that progressivity increased following a court-ordered school-finance overhaul. Rather, we show that changes in progressivity were most consistently tied to changes in student demography: As students became poorer, or more racially diverse, lawmakers created less progressive finance systems. The article concludes by discussing what these findings mean for advocates seeking to protect and advance gains in education-spending progressivity.
Holistic Evaluation of Automatic TimeML Annotators

TimeML is a scheme for representing temporal information (times, events, & temporal relations) in texts. Although automatic TimeML annotation is challenging, there has been notable progress, with F1s of 0.8–0.9 for events and time detection subtasks, and F1s of 0.5–0.7 for relation extraction. Individually, these subtask results are reasonable, even good, but when combined to generate a full TimeML graph, is overall performance still acceptable? We present a novel suite of eight metrics, combined with a new graph-transformation experimental design, for holistic evaluation of TimeML graphs. We apply these metrics to four automatic TimeML annotation systems (CAEVO, TARSQI, CATENA, and ClearTK). We show that on average 1/3 of the TimeML graphs produced using these systems are inconsistent, and there is on average 1/5 more temporal indeterminacy than the gold-standard. We also show that the automatically generated graphs are on average 109 edits from the gold-standard, which is 1/3 toward complete replacement. Finally, we show that the relationship individual subtask performance and graph quality is non-linear: small errors in TimeML subtasks result in rapid degradation of final graph quality. These results suggest current automatic TimeML annotators are far from optimal and significant further improvement would be useful.
SUBERIZATION AND WOUND-PERIDERM FORMATION IN SWEETPOTATO AND GLADIOLUS AS AFFECTED BY TEMPERATURE AND RELATIVE HUMIDITY'

An essential condition for successful storage of sweetpotato roots and gladiolus corms is that injuries received during harvest be speedily repaired and that no exposed tissues remain to act as infection courts for pathogenic organisms. In a study of the joint relation of temperature and relative humidity to infection of potato with various rot-producing fungi,^ it was noted that infection apparently did not take place if the relative humidity was very high, but if the humidity was lowered infection developed rapidly. Artschwager ^ showed that wound cork in potato developed rapidly when the humidity was held practically at saturation, but that the development of this protective layer was much belated or even inhibited at the lower humidities. It occurred to the writers that a similar relation might exist between wound-cork formation and infection in the sweetpotato, especially siace Weimer and Harter^ had already published data showing a positive correlation between woundcork formation and infection for the high humidities. Lauritzen was unable to get infection of sweetpotatoes in the temperature range of 20° to 33° C. if the relative humidity was between 95 and 100 per cent, but if the relative humidity was dropped to 80 per cent, with* temperature ranges as before, infection developed rapidly. According to Harter and Weimer,^ wound-cork formation in sweetpotato is initiated after four days (actually, as will be shown later, wound cork is formed under optimum conditions after two days), within a temperature range of 19.5° to 33° with the relative humidity practically at saturation. The lack of infection at the higher humidities may be explained, therefore, by this rapid woundcork formation which effectively shuts out pathogenic organisms. Since infection took place much more readily at the lower humidities, the question arose as to whether lower humidities were less favorable for wound-cork development, especially since positive observations to this effect had already been recorded for the potato and it was reasonable to suppose that other plants would react similarly to environmental changes. The experiments reported in this paper were initiated to ascertain the effect of lower humidities on wound-cork formation in sweetpotato roots and gladiolus corms, but during the course of the investi-
That IS-IN Isn't IS-A: A Further Analysis of Taxonomic Links in Conceptual Modelling

Ronald J. Brachman, in his basic article: “What IS-A Is and Isn’t: An Analysis of Taxonomic Links in Semantic Networks”, (1983), has analysed and catalogued different interpretations of inheritance link, which is called “IS-A”, and which is used in different kind of knowledge-representation systems. This IS-A link is seen by Brachman as a relation “between the representational objects,” which forms a “taxonomic hierarchy, a tree or a lattice-like structures for categorizing classes of things in the world being represented”, (ibid., 30). This very opening phrase in Brachman’s article reveals, and which the further analysis of his article confirms as it is done in this Chapter, that he is considering the IS-A relation and the different interpretations given to it as an extensional relation. Accordingly, in this Chapter we are considering an intensional IS-IN relation which also forms a taxonomic hierarchy and a lattice-like structure. In addition, we can consider the hierarchy provided by an IS-IN relation as a semantic network as well. On the other hand, this IS-IN relation, unlike IS-A relation, is a conceptual relation between concepts, and it is basically intensional in its character.
Impact of Technology on Human Beings

New technological innovations are taking place globally day-by-day, making an individuals’ survival and working efficiency to the maximumlimits. Technology is basically a medium through which humans are able to perform and make the things done in an efficient and faster manner.Technology more concentrates on shortening the work load and on increasing human working efficiency involving number of aspects.People today are eagerly using numbers of technological aspects, that effects the natural environment and sustainability in number of ways.Crises related to over utilization of technological aspects can contribute to degradation inphysiological, psychological factors in accordance to human brains. Significant and appropriate standards have already been implemented to curb out these negative impacts by several private and government Medical Organizations. In this paper, a survey has been conducted to discuss the challenges that can be faced while technology is projected to accomplish different tasks. A detailed survey will allow people, and researchers to opt appropriate techniques of using certain technology; and will help to lead lives towards sustainability.
Research on Online Consumption of College Students in China with Stimulate-Organism-Reaction Driven Model

 Abstract — With the development of information technology in China, network consumption is becoming more and more popular. As a special group, college students have a high degree of education and distinct opinions and personalities. In the future, the key groups of network consumption have gradually become the focus groups of network consumption. Studying college students’ online consumption behavior has important theoretical significance and practical value. Based on the Stimulus-Organism-Response (SOR) driving model and the structural equation model, this paper establishes the influencing factors model of College students’ online consumption behavior, evaluates and amends the model by using SPSS and AMOS software, analyses and determines the positive factors of marketing college students’ consumption, and provides an effective basis for guiding and promoting college student consumption.
Global Food Security – Issues, Challenges and Technological 3 Solutions

: Food security is both a complex and challenging issue to resolve as it cannot be characterized or limited by geography nor defined by a single grouping, i.e., demography, education, geographic location or income. Currently, approximately one billion people (16% of global population) suffer from chronic hunger in a time when there is more than enough food to feed everyone on the planet. Therein lies the Food security challenge to implement an ability 95 to deal with increasing food shortages, caused by a combination of waste and an ever expanding world population. At current levels prediction state that we must increase global food production by 70% on already over exploited finite infrastructures before 2050. firstly It is then to the factors affecting and the many national and international measures adopted to tackle the at and technological level.
The Use of Infographics to Enhance the English Writing Skill of Mathayomsuksa 3 Students in a Private School Context

This study aimed to investigate the effects of the use of infographics on students’ English writing skills, and to explore students’ opinions toward the use of infographics. The sample group of 50 students, obtained through cluster random sampling, was drawn from a population of 288 Mathayomsuksa 3 students at a private school in Chiang Mai, Thailand. The research instruments included lesson plans, a writing test, the pre-test and post-test, and a set of questionnaires. Statistics for data analysis included mean, percentage, standard deviation, and t-test. The results revealed that the use of infographics enhanced student's writing skills. The post-test scores were higher than the pre-test scores at the significance level of 0.05. The students had positive opinions towards the use of this media. They found writing classes utilizing infographics enjoyable, and they opined that the use of infographics raised their awareness on generating, connecting, and organizing ideas.
Intestinal parasitic infections and associated factors among HIV/AIDS patients at regional referral hospital art clinic, Northern Uganda

Intestinal parasitic infections create a huge concern in the management and care of HIV positive people in Uganda. Understanding the prevalence and associated factors is vital for proper planning and patient management. To assess the prevalence of intestinal parasites and associated factors among HIV/AIDS patients at Gulu Regional Referral Hospital, a cross-sectional study was carried out. Three hundred twenty-nine participants were recruited using simple random sampling technique on consenting. Stool specimens were examined microscopically and macroscopically for intestinal parasites. A semi-structured questionnaire was used for demographic data collection and analysis was done using STATA software version 14.0. Prevalence of intestinal parasites was 25.8%; Isolated parasite species were Entamoeba histolytic, Giardia lamblia, Cryptosporidium parvum, Ascaris lumbricoides, Hymenolepsis nana, Schistosoma Mansoni, Strongyloides stercolaris and hookworm. History of abdominal pain (AOR= 12.12, 95% CI: 11.01-14.10, p-value ˂ 0.001), diarrhea (AOR= 11.1, 95% CI: 11.03-13.16, p-value 0.003), water source (AOR= 3.12, 95% CI: 2.91-4.31, p-value 0.02), and high viral load results (AOR= 2.9, 95% CI: 1.98-3.11, p-value 0.001) were associated with intestinal parasitic infections. Intestinal parasitic infections remain a health challenge among HIV/AIDs patients in the study area; Entamoeba histolytic, Giardia lamblia, and Cryptosporidium parvum being common intestinal parasites. History of diarrhea, abdominal pains, high viral load, unreliable safe water sources were associated with diarrhea in HIV/AIDS positive people in the study area. There is a need for health sensitization with emphasize on the importance of environmental sanitation and personal hygiene and enhancement of the prevailing opportunistic infection control interventions among HIV/AIDS positive people on Antiretroviral treatment (ART). Routine deworming and stool examination should be done during follow-up visits.
Red Deer Optimization Based Grid Interactive Asymmetrical Reduced Switch Multilevel Inverter with Low Output Harmonics using Single PV Source

This paper proffers a Multilevel Inverter (MLI) topology that designed with minimum number of power switch with a single voltage source. This reduced MLI is energized by Photo Voltaic (PV) module and integrating with low voltage grid, which is cost effective with minimum number of switching devices and input voltage sources. Asymmetrical voltages are provided through series capacitors across PV boost voltage, which resulted different grading of voltage levels at the output side of reduced MLI. This output voltage has provided a smooth sinusoidal waveform than the symmetrical one. The proposed algorithm has overcome the deprivation of cascade H-bridge MLI and conventional two-level inverter with low switching loss and minimum switching stress. The varying capacitance ratio with respect to a reference value and required switching pulses are determined by the help of a new metaheuristic algorithm called Red Deer Optimization (RDO) algorithm. This algorithm has optimized the Total Harmonics Distortion (THD) of a grid tied three-phase reduced H-bridge MLI to 2.33% and has properly balanced the capacitance ratio across source voltage for which the MLI has resulted less distorted voltage and current waveforms across grid side. The performance of this new metaheuristic algorithm has been compared with Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) algorithms to prove its potency. The operation and efficiency of this proposed reduced MLI has been endorsed with the help of simulation and experimental results as well.
Artificial Intelligence (AI) Enabled Fuel Design

Fuel composition plays an important role both in efficiency and effectiveness of engines. Combined with the engine variables, fuel can span a wide range of composition space, which makes it demanding to find an optimal composition. Artificial Intelligence (AI) algorithms are attracting significant interest for predicting complex phenomenon. In this chapter, a discussion is presented on exploiting the advantages presented by machine learning algorithms for fuel formulation. The present fuel modelling scenario and a holistic approach necessary for fuel optimization is first presented. A wealth of AI algorithms are available to make use of in fuel formulation. These algorithms are discussed in line with their application to fuel formulation and the literature of the explored space in this area is presented. Additionally, a discussion is presented on how AI also helps in assisting the traditional computational fluid dynamic and chemical kinetic analysis for an elaborate study of fuels. Fuel development is just a step in the entire engine innovation cycle, and a perspective of how the AI fits in to this scenario is presented.
Are Embedding Spaces Interpretable? Results of an Intrusion Detection Evaluation on a Large French Corpus

Word embedding methods allow to represent words as vectors in a space that is structured using word co-occurrences so that words with close meanings are close in this space. These vectors are then provided as input to automatic systems to solve natural language processing problems. Because interpretability is a necessary condition to trusting such systems, interpretability of embedding spaces, the first link in the chain is an important issue. In this paper, we thus evaluate the interpretability of vectors extracted with two approaches: SPINE a k-sparse auto-encoder, and SINr, a graph-based method. This evaluation is based on a Word Intrusion Task with human annotators. It is operated using a large French corpus, and is thus, as far as we know, the first large-scale experiment regarding word embedding interpretability on this language. Furthermore, contrary to the approaches adopted in the literature where the evaluation is done on a small sample of frequent words, we consider a more realistic use-case where most of the vocabulary is kept for the evaluation. This allows to show how difficult this task is, even though SPINE and SINr show some promising results. In particular, SINr results are obtained with a very low amount of computation compared to SPINE, while being similarly interpretable.
Foliar application of calcium and boron on yield and quality attributes of strawberry

Strawberry is one of the most important crops with small fruits after grapes widespread in different regions of the world due to its many varieties and its ability to grow and adapt to different environmental conditions. The availability of calcium and boron is very important for the growth of plants as the lack of any of them lead to a significant imbalance in growth and yield. Hence, the main aim of this study to determine the effect of calcium and boron on yield and quality attributes of strawberry. This study was carried out during 2021-2022 at Vattavada village, Idukki district in Kerala. The experiment was laid out in a Randomized Block Design with 4 treatments and each treatment replicated thrice. The data recorded on various parameters viz., albinism, fruit malformation, grey mould, number of leaves per plant, number of flowers per plant, fruit setting percentage, fruit length, fruit diameter, number of fruits per plant, fruit weight, total yield per plant, fruit firmness, total soluble solids and fruit acidity were statistically analyzed. Significant differences were observed among different treatments on various yield parameters in Sweet Charlie variety of strawberry. Among the four treatments, combination of calcium and boron spray had recorded significantly the highest number of leaves per plant (45.76), number of flowers per plant (15.83), fruit setting percentage (93.44%), fruit length (39.44 cm), fruit diameter (32.94 cm), number of fruits per plant (13.86), fruit weight (13.56 g), total yield per plant (187.94 g), and also recorded lowest albinism (7.24%), fruit malformation (3.85%) and grey mould (2.14%). In quality characters significant differences were observed among different treatments in Sweet Charlie variety in strawberry. Among all the treatments, combination of calcium and boron spray had recorded significantly the maximum fruit firmness (1.55 N), fruit acidity (1.26%), and also recorded lowest total soluble solids (7.56%). Hence, our studies clearly indicated that combination of calcium and boron application can be recommended for reducing the incidence of albinism, fruit malformation and grey mould in strawberry, and to get higher yield.
TEXTURE ANALYSIS USING GABOR FILTERS FOR IMAGE CLASSIFICATION BASED ON SVM *

: The texture is an important factor in region-based segmentation of images. Texture can be seen in many images from multispectral remote sensed data to microscopic photography. Despite its importance, there is no unique and precise definition of texture. Each texture analysis method characterizes image texture in terms of the features it extracts from the image. Therefore, it depends not only on studying the images but also on the goal for which the image texture is used and the features that are extracted from the image. Gabor filters provide means for better spatial localization however their usefulness is limited in practice because there is usually no single filter resolution at which one can localize a spatial structure in natural texture. In this paper, we present a methodology based on computing a set of textural measures with Gabor filter, and then, the Gabor texture features combined with original bands of image, PCA, and NDVI, etc. were adopted as the characteristic vector of training samples for SVM, and Decision Tree classification. Finally, traditional classification schemes of Maximum Likelihood were comparatively studied.
IMAGE PROCESSING METHODS USING FOR DIAGNOSIS DIABETIC RETINOPATHY

A Diabetic eye infection is one of the serious issues around the world. That can cause major impairment to the eyes, including a permanent loss of vision. Early detection of eye diseases increase the survival rate by successful treatment. The proposed methodology is to explore machine learning technique to detect diabetic diseased using thermography images of an eye and to introduce the effect of thermal variation of abnormality in the eye structure as a diagnosis imaging modality which are useful for ophthalmologists to do the clinical diagnosis. Thermal images are pre-processed, and then Gray Level Cooccurrence Matrix (GLCM) based texture features from gray images, statistical features from RGB and HSI images are extracted and classified using classifier with various combination of features. A statistical method of examining texture that considers the spatial relationship of pixels is the gray-level co-occurrence matrix (GLCM), also known as the gray-level spatial dependence matrix. RGB is the most widely used color space , and we have effectively talked about it in the past instructional exercises. RGB represents red green and blue. What RGB model states , that each shading picture is really shaped of three unique pictures. Red picture , Blue picture , and dark picture. A normal grayscale image can be defined by only one matrix, but a color image is actually composed of three The HSI color model represents every color with three components: hue (H)