Miracle-dz/UniFAR-FTUs huggingface dataset:
Increasing returns in the life history of Columbian ground squirrels

1. We examined positive associations and trade-offs of maternal and reproductive traits in a population of Columbian ground squirrels, Spermophilus columbianus. 2. Structural size, body condition, mother's personal allocation to body mass during reproduction, and timing of littering were estimated for live-trapped reproductive females that were observed during an 8-year period, and were compared to litter mass, litter size, and average pup mass using path analyses. 3. Mothers exhibited age-structured traits that influenced reproductive patterns. Yearling mothers were significantly smaller, bred later, and had smaller litters than older females. Mothers that gained more body mass during reproduction and older mothers in good body condition that were structurally large had larger litters. 4. Early seasonal timing of littering was an important positive influence on successful reproduction by older mothers only in early breeding seasons and in years when conditions for reproduction were good for all females. 5. The number of offspring that survived to 1 year of age was most strongly associated with litter mass and litter size; date of breeding was of secondary influence, with earlier litters exhibiting greater success. 6. In general, mothers that gained the most in body mass during reproduction were concurrently more successful in weaning large litters (perhaps due to better quality of foraging habitat). 7. In addition to expected reproductive trade-offs, reproduction by Columbian ground squirrels exhibited positive associations of life-history traits that may reflect evolutionary increasing returns.
Lidar Based Intelligent Obstacle Avoidance System for Autonomous Ground Vehicles

Autonomous ground vehicles (AGVs) started occupying our day-to-day life. AGVs can be programmed to be smart with the current technological advancements. In doing so, we can apply them to assist humans in many aspects like reducing road accidents, enabling us to use cars without driving knowledge, autonomous patrolling in dangerous zones, and autonomous farming. For AGVs to operate at this level of automation, it must be equipped with sensory perception devices to be aware of its surroundings, and also, a way to perceives this data is crucial. As a first step towards this, researchers have developed a vast number of camera vision-based efficient neural network algorithms for detecting and avoiding obstacles. Unfortunately, an AGV cannot survive only with computer vision as it suffers from several effects like night driving and erroneous estimation of distance information. Camera vision and lidar vision together is suitable for AGVs to operate in all conditions like day, night, and fog. We propose a novel neural network model, which transforms the lidar sensor data into obstacle avoidance decisions, which is integrated into the hybrid vision of any AGV. Existing lidar sensor-based obstacle detection and avoidance systems like 2D collision cone approaches are not suitable for real-time applications, as they lag in providing accurate and quick responses, which leads to collisions. The proposed intelligent Field of View (FOV) mechanism replaces classical mathematical approaches, which accurately mimics the behavior of human drivers. The model quickly takes decisions with a high level of accuracy to command the AGV upon being obstructed with obstacles in the trajectory. This makes the AGV drive in obstacle rich environments without manual maneuvering autonomously.
Nåden, D. (2013). Family caregivers' experiences in nursing homes: narratives on human dignity and uneasiness. Research in gerontological nursing, 7(6), 265-272. FAMILY CAREGIVERS’ EXPERIENCES IN NURSING HOMES; NARRATIVES ON HUMAN DIGNITY AND UNEASINESS. Running headline: A life in dignity

This qualitative study is focusing on dignity in nursing homes from the perspective of family caregivers. Dignity is a complex concept and central to nursing. Dignity in nursing homes is a challenge, according to research. Family caregivers are frequently involved in their family members’ daily experiences at the nursing home. This Scandinavian cross-country study has a descriptive and explorative design. Twenty-nine family caregivers were included. A phenomenological-hermeneutic approach was used to understand the meaning of the narrated text. The interpretations revealed two main themes: “One should treat others in ways that one would like others to treat oneself” and “Uneasiness due to indignity”. The main reason for dignity was experiences as respect, confidence, security and charity. The uneasiness occurred when indignity aroused. The voices of the family caregivers are usually taciturn, but still important in nursing homes. It seems therefore important to further investigate experiences of family caregivers in the context of nursing homes. Dignity, family caregivers, nursing home, hermeneutics
Classification Techniques for Plant Disease Detection

Production of crops with better quality is the necessary attribute for the economic growth of any country. The agricultural sector provides employment to many people and accounts for major portion of gross domestic product in many countries around the world. Therefore, for enhanced agricultural productivity the detection of diseases in plants at an early stage is quite significant. The traditional approaches for disease detection in plants required considerable amount of time, intense research, and constant monitoring of the farm. However, optimized solutions have been obtained over the past few years due to technological advances that have resulted in better yields for the farmers. Machine learning and image processing are used to detect the disease on the agricultural harvest. The image processing steps for plant disease identification include acquiring of images, pre-processing, segmentation and feature extraction. In this review paper, we focused mainly on the most utilized classification mechanisms in disease detection of plants such as Convolutional Neural Network, Support Vector Machine, KNearest Neighbor, and Artificial Neural Network. It has been observed from the analysis that Convolutional Neural Network approach provides better accuracy compared to the traditional approaches.
The effects of dietary protein levels on the carcass composition of starter and grower broilers

Carcass analusis of most economical parts of broilers were studied after they were fed with different protein levels of 16, 18, 20 and 23% for the starter period and 16, 18 and 20% for the grower period. The energy value of the feed was constant at 3,200 kcal ME/kg. The results for the starter and grower broilers showed similar pattern of responses. There were significant increased in weight gain, feed intake, protein intake, while there were significant decrease in the feed conversion ratio(FCR), abdominal fat and carcass fat when dietary protein increased. For the economical parts of the carcass, most of the fats were found in the thigh meat, while the lowest was found in the breast meat. The protein levels did not influence the meat production of the breast, drumstick and thigh portion. Increasing the protein intake, increased the broiler performance in relation to increased protein content of the breast, drumstick and thigh meat. The different fat contents of the meat might be due to differences in the rate of pipogenesis and fat deposition of the meat.
Recommendation of Price on Airbnb using Machine Learning

Airbnb’s rental property prices are challenging because they determine how many customers there are. Customers, on the other hand, need to evaluate the offer price with minimal knowledge of the optimal value of the accommodation. This white paper aims to develop a reliable pricing model that uses machine learning and natural language processing techniques to assess prices by providing minimum available information about prices for both real estate owners and customers. Attributes, rooms, and bed features made up the predictors and created the prediction model using a variety of methods, from linear regression to root mean square error evaluation was used for creating the prediction model.
Studies on the protein metabolism of cestodes

The dry weight and nitrogen content of Hymenolepis diminuta were studied after a period of 15 days‘ growth in rats receiving different diets. The special diets were fed during the last 7 days of this period, that is, while the major part of growth is occurring but before shedding proglottids. Replacement of all the protein (casein) of the diet by carbohydrate resulted in greater development of the worm. However, replacement of casein by fat had no effect on worm development, indicating that removal of protein is not a significant factor, whereas addition of carbohydrate is effective. Since exchange of casein by the nutritionally incomplete protein zein did not affect worm development significantly, protein quality appears not to be a factor in growth of H. diminuta. The addition of tryptophan and lysine to the meal containing zein, in order to raise its nutritional value to that of casein, did not influence the growth of the parasite. However, the feeding of the same amounts of these two amino acids at times other than those of giving zein depressed the growth of the parasite. This was not due to type of protein (zein) fed in the rest of the diet, since a similar phenomenon occurs when casein is the dietary protein, or when a protein-free diet rich in carbohydrate is given. Addition of these amino acids, singly, either to diets containing protein or deficient in protein, had significant actions on worm growth, which was sometimes stimulated and in other circumstances reduced. The nitrogen balance of the host was unaffected by the worm burden. We are deeply indebted to Dr C. A. Hopkins for providing facilities, for infection of rats with the cestode, and for his helpful advice. Miss M. Cowan provided skilled technical assistance during the feeding of the animals and analysis of the host and parasite tissues. One of us (D.F.M.) gratefully acknowledges the Award of a Commonwealth Bursary from the Royal Society and the Nuffield Foundation.
The buoyancy of plankton diatoms: a problem of cell physiology

Observations on pure cultures of diatoms and the results of centrifuge experiments showed that under optimal conditions the vegetative cells have the same specific gravity as sea water. The specific gravity of resting spores is significantly higher than that of sea water. Hence the specific gravity of the cell sap which fills the bulk of the vegetative cell and is expelled during formation of the resting spore is lower than that of sea water. The reduced weight (i. e. weight underwater) of resting spores of Ditylum was measured by means of the Cartesian diver balance. The mean value obtained was 0·00312γ per spore. From calculations of the volume difference between the vegetative cell and the resting spore the specific gravity of the cell sap was estimated at 1·0202, i. e. 0·0025 less than that of the sea water used. It is suggested that the mechanism underlying buoyancy in plankton diatoms is similar to that involved in the flotation of Halicystis and consists in the maintenance of very low concentrations of divalent ions in the cell sap, the result of a steady expenditure of energy.
Application of Machine Learning for Prediction of Lung Cancer using Omics Data

Cancer is one of the deadly diseases across many countries. However, cancer can be cured, if detected at an early stage. Researchers are working on healthcare for early detection and prevention of cancer. Medical data has reached its utmost potential by providing researchers with huge data sets collected from all over the globe. In the present scenario, Machine Learning has been widely used in the area of cancer diagnosis and prognosis. Survival analysis may help in the prediction of the early onset of disease, relapse, re-occurrence of diseases and biomarker identification. Applications of machine learning and data mining methods in medical field are currently the most widespread in cancer detection and survival analysis. In this survey, different ways to detect and predict lung cancer using latest Machine learning algorithms combined with data mining has been analyzed. Comparative study of various machine learning techniques and technologies has been done over different types of data such as clinical data, omics data, image data etc.
EMPIRICAL STUDIES ON THE IMPACT OF SOFTWARE CUSTOMIZATION ON QUALITY ATTRIBUTES: A SYSTEMATIC REVIEW

Software needs to deliver acceptable levels of quality, whilst meeting the functional demands of users. This need is gaining more consideration in Enterprise Resource Planning (ERP) and multi-tenant software. This study investigated the effect of software customization on external quality attributes via four pertinent primary studies, which were summarized, aggregated, discussed and presented through a systematic literature review. The primary studies in this review were chosen through the application of inclusion and exclusion criteria to applicable articles published during the period 2000-2016; they were analysed using research questions that focused on software customization, software quality attributes and measures, approaches, and impact results. The results revealed that each primary study had been applied in the context of ERP and demonstrated that different types of customizations can have various effects on particular quality attributes. Accordingly, further research is needed to determine the impact of customization on each external quality attribute.
Environmental Prints in Children Nasal Epithelium Living at the Attica Basin

The metropolitan area of Athens is facing to a serious air pollution problem. The mucosa of the nasal epithelium is highly exposed through breathing to all the airborne irritating agents that exist in the urban air. Therefore, the morphological pattern of this mucosa is greatly affected. The study aimed to investigate histopathological alterations in the nasal mucociliary respiratory epithelium of healthy children, in relation to the lodging at the Attica basin. Samples were collected at schools from three different municipalities, north and near to the banks of the Kifissos River, and from a control population who lived in a low-polluted area, apart from Attica basin. The children’s age ranged from 11 to 12 years. 49 samples were collected from exposed areas (11from the Municipality of Philadelphia, 19 from the Municipality of Kifisia, and 19 samples from the Municipality of Kryoneri) and 12 from the control area. Immunoistochemical staining was used to evaluate the expression of p53 protein. The results were analyzed with IBM SPSS Statistics 20 for Windows. Pearson's Chisquare and Friedman test were used to compare nasal epithelium changes between exposed and control areas. No statistically significant differences of the histopathology parameters were observed between exposed groups. Pearson Chi-square test shows a significant difference in the positive immunoreaction of p53 between control and exposed areas (p = 0,000). Friedman test shows that, from the thirteen examinee parameters for each municipality, eight of them were related with a confidence coefficient p = 0,000. None of the 49 exposed children to the Athens environment had normal nasal epithelium, in contrast with the control area. The fact that no statistical differences between the histopathology parameters and the municipalities was observed may confirm that people living at the Attica basin have the same probability of developing alterations in nasal epithelium. Key-Words: Nasal epithelium, nasal biopsies, children exposure, schools, Attica basin, Attica municipalities, Kifissos River, air pollution, histopathology parameters, p53. Funding sources: No funding sources support the work described in the manuscript. Statement of approval: This study was approved by the Ministry of Education, Lifelong Learning and Religious Affairs of Greece and by the Bioethical Committee of the Medical School of the University of Athens (NKUA). Also, the parents of the children gave written consent for the research, after being clearly informed about the objectives of the study.
The Phenotypic Relationship of a Clonal Line to Its Population of Origin: Rapid Embryonic Development in an Alaskan Population of Rainbow Trout

Abstract Homozygous clonal lines of rainbow trout Oncorhynchus mykiss are currently being used for genetic analysis of several important quantitative traits, but the relationship between a unique clonal phenotype and the phenotype of the source population remains unclear. We aimed to determine whether the accelerated development rate previously observed in a clonal line derived from Swanson River, Alaska, rainbow trout was also represented in the source population. Development rates of rainbow trout from three geographically distinct populations (the Swanson River, Skookumchuck River, Washington, and American River, California) were compared across a range of temperatures. The Swanson River rainbow trout had an accelerated rate of development at all temperatures, and quantitative genetic analyses indicated a genetic basis for the differences in development rate among populations. These results indicate that the clonal line derived from the Swanson River population is a reflection of an evolved phenotype i.
Does Adam Smith’s Invisible Hand Work for FinancialMarkets: Comments

Adam Smith theory of the Invisible Hand is fundamentally flawed. The neoclassical theory based on it relies on market models in which economic agents interact with the market forces that are not governed by Universal Law of Nature; such models ignore correlations that lead to booms and depressions. To prove rigorous theorems financial economists also assume that market fluctuations follow a certain statistical distribution a la a thermodynamic equilibrium approach. Do they really score a major breakthrough? No the dominant ‘equilibrium principle’ of the market is only a hope, not a reality: It lacks proper empirical underpinning. Statistics and mathematics do not help.
Identification of Diabetic Retinopathy from Color Fundus Images using Deep Convolutional Neural Network

Existing methods on retinal disease detection are mostly depends on lesion detection techniques or multiple instance learning framework. However extensive research efforts fail to address effective representations of the different lesions from fundus images. In this paper, a innovative techniques is offered built on pre-examined entirely convolutional neural network (CNN) over and done with transfer learning. The proposed method utilizes the effective learning from recent deep CNN models with use of SVM classifier at the end. Meanwhile, additional retinal image pre-processing technique is applied for the better classification results. The improved result has contributed to the area of computer aided diagnosis for retinal screening system. Extensive experiments have been conducted on Messidor and IDRiD database with desired obtained accuracy of 96.29 % and 94.82 %. The proposed method supports retinal disease screening effectively by deep learning methods.
Examination of Implicit Interactivity in Wiki-based Learning in University

The arrival of the Web 2.0 age, which is characterized by such key words as participation, sharing and openness, provides a learning environment in which both instructors and students can experience interactivity. In the educational area, we are particularly witnessing a growing interest in the social software like Wiki as one of the communication tools that reflects the characteristics of Web 2.0 and focuses on the interactivity with others. Based on this background, this study aims to examine into the meanings of interactivity inherent in the Wiki-based learning by studying such cases where Wiki is being used as a learning tool. For the purpose of our study, we practiced the Wiki-based learning method on the study subjects of the 17 junior students from U- University and 18 junior students from K- University during their 2009 fall semester teacher training courses. Through a comprehensive analysis of the questionnaires, interviews, Interactivity Measurement Diagram, examinations on the Wiki uses, Daily Self-reflection Records, and any other materials collected throughout the program, we could garner the following results: First, most of the students acknowledged that the use of Wiki was a useful communication means and helped promote their interactivity during their learning activities. Second, the interactivity of the Wiki-based learning was found to be more dynamic in the team-based projects or the community-based Wiki uses than in the instructor-oriented cases. Third, the Wiki-based learning is judged effective in expanding the scope of thinking and improving the learning capabilities through the collaborative knowledge-building process. The educational employment of the social software like Wiki in this web 2.0 age has great potentials for the true establishment of the learner-oriented learning environment, which has long remained at a standstill.
Development of a modified Britton improved linearity in the alkaline pH region

Britton-Robinson buffer is a multi-buffer system acid. Although this buffer system is known region (pH 9–12) is poor. Searching alkaline region, we found that glycine ( the pH titration curve. The pH titration formula of the improved this report. The pH-dependent activities of electrolyte balance, were investigated using the improved buffer, and the results those measured with the typical Britton
EFFECTS OF DATE OF WEANING ON SUBSEQUENT PERFORMANCE OF BEEF COWS AND THEIR FEMALE CALVES

1233 April/May born calves were weaned either on 30 Sept. (EW) or 31 Oct. (LW) to assess the effects of weaning date on subsequent performance of their dams and female calves. Cows in the EW group lost less weight than those in the LW group in the month of October (0.003 vs. 0.48 kg d−1, P < 0.05). Dam's breed group, year and the interaction between year and age of dam also had significant effects on weight change during October. Cows generally lost weight between weaning and the next calving and the two weaning groups were similar in body weight at calving and reproductive performance. The reproductive performance of the EW and LW female calves were also quite similar. It can be concluded that weaning April/May born calves in September rather than October would not influence the subsequent production of the dams or their female calves, but would probably reduce their maintenance requirements as they enter the cold season in better condition. Key words: Weaning date, beef cows, reproduction, weight changes
EFFECTIVENESS OF K-MEANS CLUSTERING TO DISTRIBUTE TRAINING DATA AND TESTING DATA ON K-NEAREST NEIGHBOR CLASSIFICATION

One of the constraints in classification is how to divide the dataset into two parts, training and testing which can represent every data distribution. The most commonly used technique is K-Fold Cross Validation which divides data into several parts and alternately into training data and testing data. In addition, the commonly used technique is to divide data into percentage form (70% and 30%), also become an option in data mining research. K-Means is a grouping algorithm which able to maximizes the effectiveness of distributing data in classification. The experiments performed using K-Means Clustering against K-Nearest Neighbor (K-NN) which was validated by Confusion Matrix have the highest accuracy of 93.4%, it is higher than the K-Fold Cross Validation data distribution technique for each experiment using data Education Management Information System (EMIS) as well as random data. The concept of distributing data in groups can be a representative to each member and increase the accuracy of classification algorithm, although the experiment only applied 70% of training data and 30% of testing data in each group.