Miracle-dz/UniFAR-FTUs huggingface dataset:
SORRY, DARWIN:-CHEMISTRY NEVER MADE THE TRANSITION TO BIOLOGY

The term biology is of Greek origin meaning the stu dy of life. On the other hand, chemistry is the science of matter, which deals with matter and its properties, structure, composition, behavior, reactions, interactions and the changes i t undergoes. The theory of abiogenesis maintains that chemistry made a transition to biolo gy in a primordial soup. To keep the naturalistic ‘inanimate molecules to human life’ ev olution ideology intact, scientists must assemble billions of links to bridge the gap betwee n the inanimate chemicals that existed in the primordial soup and anatomically modern humans. Eve n though the proponents of a natural origin of life expressed much optimism for providin g their theories, presently there is a detailed compilation of information seriously questioning th is doctrine. This reductionistic ideology has always failed to answer two simple questions: (1) W hat is the minimum number of parts that are essential for a living organism to survive? (2) By what mechanism do these parts get assembled together? Evolutionists say a series of prebiotic p rocesses and developments guide networks of dynamically linked small molecules and amphiphiles to form biological macromolecules, membraneous compartments, and finally primitive cel ls. However, none of these proposed pathways to life appears to be credible. The contin uous advancement in various fields of science are not only providing major challenges to reductio nistic ideology but are supplying increasing evidence for a systemic concept of life as an organ ic whole. Several leading researchers in the field of ‘origin of life’ are continually concludin g that there are major scientific problems attached with all existing naturalistic ‘origin of life’ hypothesis. Only by taking into account all biological activities collectively as a system can a satisfactory elucidation of the living state be realized. In this present paper an attempt has been made to present a few significant challenges to the theory of abiogenesis based on the peer reviewe d sci ntific literature. Subsequently, a nonreductionistic concept of life as a system is propo sed as an alternative for resolving some of the problems inherent in origin of life research.
CONTEMPORARY GLOBALIZATION AND TERITORRIALISATION OF SOCIETY: IDENTITY DIMENSION IN SERBIA**

Paper starts with the link between contemporary globalisation and processes of de-territorialisation and re-territorialisation of society, which helps understanding the separation of social from state territoriality and increasing importance of other territorial scales (both sub national and supranational) in a numerous social issues. The paper aims to analyse identity dimension of these processes in two aspects. Firstly, it focuses on changing territorial identity of individuals regarding the weakening of their attachment to the nation-state and strengthening of their attachment to other territorial scales, primarily to the immediate local environment and then to supranational one (as EU). Secondly, re-territorialisation of citizens’ identity (increasing attachment to place of living in an open and relational manner) is analysed as potentially valuable local developmental resource within globalising societies, as emphasized in EU territorial agenda. Both issues are important for Serbia, as well as for other European post-socialist societies, whose globalisation and recent de-re-territorialisation take place under the significant influence of EU. The analysis relies on empirical data obtained through questionnaire research conducted on a representative sample (N=2557) of citizens in Serbia by Institute for Sociological Research at the Faculty of Philosophy University of Belgrade, in spring 2012. The research findings show that territorial identity of citizens in Serbia develops in accordance to the principles of selective associations and multiple loyalties, but that new localism and glocalism as desirable development resources still have not been sufficiently profiled.
Extração e Comparação de Características Locais e Globais para o Reconhecimento Automático de Imagens de Faces

Recent studies on face recognition have highlighted that local and global features are both useful depending on the application context. This paper proposes and implements a comparison between the Local Binary Pattern (LBP) and Principal Components Analysis (PCA) techniques in order to understand the behavior of each feature extraction method when using pre-processed and previously spatially normalized face images. Our results show a good performance of LBP only in the experimental situations where the training set is composed of individuals in frontal pose with necessarily the neutral facial expression available. However, using a training set with distinct facial expressions randomly chosen the PCA has been more efficient in classifying the top ranked individuals.
The Physical Fitness Levels Analysis of University Students

Physical fitness defined as the ability to perform daily activities without feeling fatigue. This is descriptive quantitative study using a survey method. Aiming to determine and to describe the physical fitness levels of sports science student at Universitas Negeri Semarang. Randomize sampling technique was used in this study (n = 32) both male and female. Multistage Fitness Test (MFT) was performed to test the level of physical fitness for each subject. Results showed that from female students 23.81% of subjects have low physical fitness level, 28.57% have sufficient physical fitness level, 33.33% have good physical fitness level, and 14.29% have excellent physical fitness level, while from male students 63.64% have adequate physical fitness level, 18.18% have good physical fitness level, and 18.18% have excellent physical fitness level. We concluded although there are some students in low physical fitness level, but taking the average university students are in good level. To improve this phenomenon getting better in the future, we strongly suggest to be active physically either by doing more physical activities or
Reconstruction of Image Sequences From Ungated and Scanning-Aberrated Laser Scanning Microscopy Images of the Beating Heart

Fluorescence laser-scanning microscopy is a well-established imaging technique in biology, available in many imaging facilities to investigate structures within live animal embryos such as zebrafish. Laser scanning microscopes (LSM) are limited when used to study dynamic heart morphology or function. Despite their ability to resolve static cardiac structures, the fast motion of the beating heart introduces severe artifacts in the scanned images and gating the acquisitions to the heartbeat is difficult to implement on traditional microscopes. Furthermore, although alternative high-speed imaging instruments exist, they are not widely available (due to cost or hardware complications), putting dynamic cardio-vascular imaging off-limits for many researchers. Here, we propose a method that allows imaging the beating heart on conventional LSMs. Our approach takes a set of images containing scanning aberrations, each triggered at an arbitrary time in the cardiac cycle, and assembles an image sequence that covers a single cardiac heartbeat. The steps are: (i) frame sorting by solving a traveling salesman problem; (ii) heartbeat duration estimation; and (iii) scan-delay compensation via space-time resampling. We characterize the performance of our method on synthetic data under several light intensities and scanning speeds. We further illustrate our method's applicability on experimental images acquired in live zebrafish larvae, and show that the reconstruction quality approaches that of fast, state-of-the-art microscopes. Our technique opens the possibility of using LSMs to carry out studies of cardiac dynamics, without the need for prospective gating or fast microscopes.
Memory Management of Manycore Systems

This thesis project is part of the MANY-project hosted by ITEA2. The objective of Many is to provide developers with tools for developing using multi and manycore, as well as to provide a knowledge-base about software on manycore. This thesis project has the following objectives: to investigate the complex subject of e ectively managing system memory in a manycore environment, propose a memory management technique for implementation in OSE and to investigate the Tilera manycore processor TILEPro64 and Enea OSE in order to be able to continue the ongoing project of porting OSE to TILEPro64. Several memory management techniques were investigated for managing memory access on all tiers of the system. Some of these techniques require modi cations to hardware while some are made directly in software. The porting of OSE to the TILEPro64 processor was continued and contributions where made to the Hardware Abstraction Layer of OSE. Acknowledgements I would like to start by thanking all the people who helped me during this thesis. At KTH I would like to thank my examiner Ingo Sander and at Xdin I would like to thank Barbro Claesson and Detlef Scholle for giving me the chance to work on this project. At Enea I would like to thank OSE chief architect Patrik Strömblad for his assistance as well as Peter Bergsten, Hans Hedin and Robert Andersson for helping me to evaluate memory technologies in OSE and Anders Hagström for guiding me through the intricate details of OSE's interrupt-handling. Lastly I would like to thank all my friends who have helped me by proofreading this report and special thanks to Chris Wayment for scrutinizing the language of this report.
Profile of Physical Conditions from UNNES Football Club at Liga Mahasiswa Piala MENPORA 2019

This research aims to determine the profile of the football athlete's physical condition. This type of research is quantitative descriptive research. The sampling technique in this research used a total sampling technique. The instruments used: 1) the hand dynamometer test, back and leg dynamometer test; 2) sit-ups, push-ups, and squat jumps; 3) 50 meter running test; 4) the Illionis Agility run test; 5) Sit and Reach test; 6) vertical jumps test, 7) MFT test. Analysis of the data used is quantitative descriptive analysis with percentages. Based on the analysis of the data, it can be concluded that: 1) the average strength of arm muscle in pushing is in the medium category, 2) the average strength of arm muscle in pulling is in the medium category, 3) the average strength of back muscle is in the medium category, 4) the average strength of leg muscle is in the less category, 5) the average endurance of arm and shoulder is in the good category, 5) the average endurance of muscle abdominal is in the less category, 6) the average endurance of leg muscles is in the medium category, 7) the average speed is in the medium category, 8) the average agility is in the medium category, 9) the average flexibility is in the excellent category, 10) the average of leg muscle power is in the medium category, and 11) the average of Cardiopulmonary Endurance is in the very poor category. Keywords— Physical Conditions, Football, Liga Mahasiswa Piala MENPORA
Jet Flow Structure under the Perturbation of Two Unsteady Microjets

The manipulation of turbulent jet mixing has great potential benefits in various industrial applications. This work reports an experimental investigation on the active control of a turbulent round air jet using two unsteady radial microjets. Two microjets were placed at diametrically opposite locations upstream of the nozzle exit. The Reynolds number was 8,000. The flow rate ratio Cm and excitation frequency ratio fe/f0 of the microjets to the main jet were varied over the ranges of 0 – 16% and 0 – 1.4, respectively, where fe was the excitation frequency of unsteady microjets and f0 the preferred-mode frequency in the uncontrolled jet. It has been found that, given fe/f0 ≈ 1, jet mixing can be greatly improved with a small Cm. The flow physics is explored based on flow visualization technique in two orthogonal diametrical planes through the geometric axis of the flow, as well as a number of cross-sectional planes normal to the axis. It has been found that strong entrainment is predominant in the injection plane of microjets. In contrast, rapid spreading occurs in the orthogonal non-injection plane. A close examination of flow visualization photographs unveils that a number of structures are sequentially ‘tossed’ out along the radial direction in the noninjection plane, which is accompanied by a strong ejection of jet core fluid, often in the form of one pair of mushroom-like counter-rotating structures and one pair after another. The finding is distinct from previously reported changes in the flow structure under the manipulation of steady microjets, tabs and other techniques. A conceptual model of the flow structure under the excitation of two unsteady microjets is proposed for the first time.
International Conference on Trends in Agricultural Engineering 7-9 September 2016, Prague, Czech Republic ESTIMATION OF SOIL PENETRATION RESISTANCE USING GENERALIZED REGRESSION NEURAL NETWORKING

Soil compaction is a major problem affecting negatively the soil physical, chemical and biological properties and impedes plant root growth. Soil penetration resistance values should be collected from many points of the production area to determine the effects of these problems on plant growth. Soil penetration value collection from large production areas is time-consuming and tedious application for researchers. Also, the number of measurement points to what extent will be sufficient to evaluation on whole production area is not clear. To eliminate this ambiguity, soil penetration values of the unmeasured points should be estimated to evaluate the whole area. Artificial neural networks are one of the most popular mathematical computing and modelling method used to estimate unknown data values with known data values. In this study, we collected 1603 samples of geographical position and soil penetration value from 40 cm depth within the 20 ha field. From the 1603 values, 24% records were selected for testing and the remaining 76% records were used for educating and validating. Soil penetration values of the unmeasured points were estimated using Generalized Regression Neural Network (GRNN) method in Matlab. In addition to mean squared error (MSE), root mean square error (RMSE), mean absolute error (MAE) and R 2 has been also used for evaluation of prediction accuracy on GRNN method. The results showed very good agreement between the predicted and the measured real values of soil penetration resistance.
Stock Price Trend Forecasting and Stock Selection using Supervised Learning Methods

In this paper, we are going to present and review a more feasible method to predict the stock movement with higher accuracy. The first thing we have taken into account is the dataset of the stock market prices from the previous year. The dataset was pre-processed and tuned up for real analysis. Stock market prediction is an act of trying to determine the future value of a stock other financial instrument traded on a financial exchange. This paper explains the prediction of a stock using Machine Learning. The technical and fundamental or the time series analysis is used by most of the stockbrokers while making the stock predictions. The programming language is used to predict the stock market using machine learning is Python. In this paper, we propose a Machine Learning (ML) approach that will be trained from the available stocks data and gain intelligence and then uses the acquired knowledge for an accurate prediction. In this context this study uses a machine learning technique called Support Vector Machine (SVM) to predict stock prices for the large and small capitalizations and in the three different markets, employing prices with both daily and up-to-the-minute frequencies.
Plasmonic Materials

We provide an overview of the way in which different approaches to nanostructuring metals can lead to a wealth of interesting optical properties and functionality through manipulation of the plasmon modes that such structures support, a field known as plasmonics. The increasing interest in plasmonics derives in large measure from the interplay between better fabrication techniques and an awareness of the potential that controlled plasmon modes have to offer. The combination of nanometer‐scale fabrication techniques and increasingly sophisticated numerical modeling capabilities thus enables a significant advance in our understanding of the science underlying plasmonics. Here, we survey some of the different structures that have been explored. We hope that this Review will spur others to continue the exploration of this fascinating topic.
Targeting the Immunoproteasome in Health and Disease

68 Introduction . 69 Results . 70 EAE induction in immunoproteasome-deficient mice. 70 An LMP7-selective inhibitor prevents symptoms of EAE. 70 LMP7 inhibition prevents brain and spinal cord inflammation. 72 Therapeutic treatment with ONX 0914 inhibits progression of MOG35-55-induced EAE. 75 ONX 0914 blocks differentiation to autoreactive T cells. 77 ONX 0914 reduces clinical symptoms in the PLP139-15-induced relapsing-remitting EAE model in SJL/J Mice. 77 Discussion . 79 Material and Methods . 82 Supplementary information . 87 CHAPTER III: LCMV-INDUCED MENINGITIS . 88 1. Inhibition and deficiency of the immunoproteasome subunit LMP7 attenuates LCMVinduced meningitis . 88 Abstract . 89. 89
Greentech homophily and path dependence in a large patent citation network

We propose a method to identify the main technological trends in a very large (i.e., universal) patent citation network comprising all patented technologies. Our method builds on existing literature that implements a similar procedure, but for much smaller networks, each covering a truncated sub-network comprising only the patents of a selected technology field. The increase of the scale of the network that we analyse allows us to analyse so-called macro fields of technology (distinct technology fields related by a coherent overall goal), such as environmentally friendly technologies (Greentech). Our method extracts a so-called network of main paths (NMP). We analyse the NMP in terms of the distribution of Greentech in this network. For this purpose, we construct a number of theoretical benchmark models of trajectory formation. In these models, the ideas of homophily (Green patents citing Green patents) and path dependency (the impact of upstream Green patents in the network) play a large role. We show that a model taking into account both homophily and path dependence predicts well the number of Green patents on technological trajectories, and the number of clusters of Green patents on technological trajectories.
Language Development During Interstellar Travel

This paper explores the consequences that language change might trigger in the languages of crew members during a long journey in space or interplanetary settlement. Languages drift apart as communities grow more isolated from each other, so the long isolation of a traveling community may lead to enough difference to render its language unintelligible to the original community it left. This problem may compound as later vessels bring new crews with their own changed languages to mix with those from earlier crews. We discuss various aspects that contribute to language change, through comparison to historical Earthbound cases involving some of these aspects, such as the Polynesian settlement of far-flung Pacific islands, and dialect development in relatively isolated European colonies. We also weigh the effects of multilingualism amongst the crew, with or without a common lingua franca in use, as well as the effects of time and the role that children play in language change and creation. As we lay out ∗Corresponding author. E-mail: punske@siu.edu possible outcomes, we also suggest possible methods of shaping this development within limits.
Facial Attributes Analysis and Applications

Facial Attributes Analysis and Applications Xudong Liu Facial attributes are one of the most powerful descriptors for personality attribution. In the area of computer vision, researchers have worked on the extraction and use of attributes in face recognition. Facial attribute recognition is conventionally computed from a single image. In practice, it is quite common to capture multiple still images for each subject or to acquire a video of a subject with a number of image frames. Thus it is not rare to encounter the situation of having multiple still images or video frames of the same subject. Then it is quite natural to request a unique set of attributes about the subject given multiple face images. Naturally, how to compute the attributes given multiple images of the same subject? Firstly, we explore whether the inconsistency exists among the attributes computed from multiple face images of the same subject. The inconsistency can be caused by the variations in images, such as the face image quality changes. Then we develop methods in view of probabilistic confidence and image quality to address the inconsistency. Experimental results show that the proposed methods can handle facial attribute estimation on either multiple still images or video frames, and can correct the incorrectly annotated labels. In addition, by computing the correlation between the facial attributes and the beauty score, we developed an application about mining semantic descriptions from facial attributes for beauty understanding. The facial beauty description is constructed from facial attributes. This is a totally data-driven method to address facial beauty instead of the psychology study. After analyzing beauty features, we adopt these features to the original facial images for testing the beauty difference. Experimental results indicate that the beauty semantics are reasonable and beneficial for the beauty modification.
Homomorphic Encryption Survey Paper

Homomorphic Encryption (HE) allows for computations on data in the encrypted domain. It provides the opportunity to upload encrypted data sets to a cloud service with privacy concerns and perform operations as advanced as machine-learning-related tasks. In this paper, we will give an overview of existing HE methods and then we will focus on recent attempts to do machine learning using HE.
Patient Blood Management – the importance of hemoglobin measurement and minimizing phlebotomy-associated iatrogenic blood loss

Transfusion of donated (allogenic) red blood cells is of undoubted life-saving benefit to those suffering rapid and massive blood loss (hemorrhage) due to major trauma, or complications during surgery and childbirth. However, the procedure is not without risk, and accumulated evidence over the past 2 decades has confirmed that the benefit of red-cell transfusion is not as clear-cut in other, less dramatic clinical contexts associated with anemia.
Full Duplex in a Military Scenario Feasibility of Practical Implementation

In order to achieve Full Duplex (fd) communication, currently studied solutions for the commercial sector rely on advanced Self-Interferece Cancellation (sic) techniques to remove the transmitted signal from the received one. This thesis expands the research of these techniques by evaluating their potential usage in military communication scenarios where requirements and conditions are distinct, firstly, by identifying, categorizing and describing a set of previously proposed sic techniques and secondly, by performing a comprehensive simulation and analysis of two suggested sic techniques as part of a fd transceiver. Though the majority of the considered sic techniques was determined to be potentially implementable in military fd transceivers, some frequency-dependent techniques and techniques prohibiting omnidirectional communication could not be used. The simulation and analysis of the two suggested sic techniques show that under certain conditions, such as limited transmission power and/or reflective environment, close to complete suppression could be realized even with high nonlinear distortion in the transmit chain.