Miracle-dz/UniFAR-FTUs huggingface dataset:
Why Weren ’ t Ants the First Astronauts ?

Ants are fantastic animals. For 40 millions years they have developed cultural skills such as joint parental care, joint hunting, cooperation and labor division, cattle husbandry, and agriculture. In biological terms, they form superorganisms where individual ants act like cells in an organism. Based on their cooperative skills they are the pre-dominant life form in their ecological niches and resemble roughly the same total biomass as humans do. What impresses on the one hand, can also look very disappointing on the other. Humans developed large-scale collaborative skills significantly later; for example human agriculture evolved around 10 000 years ago. That being said, it is humans who have invented telephones, computers, and the Internet, and who have visited the Moon. In this article we use our insights on Internet and Web technology to explain this anomaly. We also project forward from this proposed explanation to consider the potential further developments embodied in a perceived new superorganism, a ‘brain for all mankind’ which humans are developing for the first time in their history.
Exploring Action Recognition without using Deep Learning

The goal of this report is to explore action recognition without using deep learning methods. Deep learning has brought about tremendous change in the fields of computer vision and machine learning in the past decade. Convolutional neural networks (CNNs) and the algorithms developed have achieved high accuracy on multiple tasks such as semantic segmentation, image classification, action recognition to name a few. However, since the rise of deep learning, not a lot of papers have shown proper comparison results with non deep learning methods for specific tasks. In this report, I will use some traditional computer vision methods for action recognition and compare their results with the state-of-the-art deep learning method. The experiments are run on the famous JHMDB dataset.
Characterizing Power and Energy Efficiency of Legion Data-Centric Runtime and Applications on Heterogeneous High-Performance Computing Systems

The traditional parallel programming models require programmers to explicitly specify parallelism and data movement of the underlying parallel mechanisms. Different from the traditional computation-centric programming, Legion provides a data-centric programming model for extracting parallelism and data movement. In this chapter, we aim to characterize the power and energy consumption of running HPC applications on Legion. We run benchmark applications on compute nodes equipped with both CPU and GPU, and measure the execution time, power consumption and CPU/GPU utilization. Additionally, we test the message passing interface (MPI) version of these applications and compare the performance and power consumption of high-performance computing (HPC) applications using the computation-centric and data-centric programming models. Experimental results indicate Legion applications outperforms MPI applications on both performance and energy efficiency, i.e., Legion applications can be 9.17 times as fast as MPI applications and use only 9.2% energy. Legion effectively explores the heterogeneous architecture and runs applications tasks on GPU. As far as we know, this is the first study to understand the power and energy consumption of Legion programming and runtime infrastructure. Our findings will enable HPC system designers and operators to develop and tune the performance of data-centric HPC applications with constraints on power and energy consumption.
Systems analysis of a fast growing N2-fixing cyanobacterium for production of advanced biofuels and nitrogen-containing petrochemical replacement compounds

Anabaena sp. ATCC 33047 is heterocystous cyanobacterium that thrives under very high light intensities and exhibits fast growth both in the presence and absence of fixed nitrogen, traits that make this strain an attractive platform for the cost effective production of nitrogen-rich compounds. The strain was known to be genetically intractable and hence not utilized in molecular and synthetic biology studies. During the course of this project we developed a genetic manipulation system that enabled us to make targeted modifications in its genome. We further characterized one of the modified strains, which shows greatly enhanced rates of nitrogen fixation. We also developed a genome scale metabolic model, iAnC892, for Anabaena 33047 to identify genetic interventions to overproduce valerolactam and caprolactam. Phycobilisomes (PBS) are large antenna protein complexes in cyanobacteria that harvest light and funnel the energy to the photosynthetic reaction centers. When subjected to nitrogen deficient growth conditions, heterocystous cyanobacteria exhibit transient PBS degradation mediated by the NblA protein. As nitrogen fixation commences, PBS is resynthesized back to their normal levels in vegetative cells, but their abundance remains low in AD P TP N2ase
Hughes Mef 2 Pg 1 Mef 2 and the skeletal muscle differentiation program

Mef2 is a conserved and significant transcription factor in the control of muscle gene expression. In cell culture Mef2 synergises with MyoD-family members in the activation of gene expression and in the conversion of fibroblasts into myoblasts. Amongst its in vivo roles, Mef2 is required for both Drosophila muscle development and mammalian muscle regeneration. Mef2 has functions in other cell-types too, but this review focuses on skeletal muscle and surveys key findings on Mef2 from its discovery, shortly after that of MyoD, up to the present day. In particular, in vivo functions, underpinning mechanisms and areas of uncertainty are highlighted. We describe how Mef2 sits at a nexus in the gene expression network that controls the muscle differentiation program, and how Mef2 activity must be regulated in time and space to orchestrate specific outputs within the different aspects of muscle development. A theme that emerges is that there is much to be learnt about the different Mef2 proteins (from different paralogous genes, spliced transcripts and species) and how the activity of these proteins is controlled.
Investing for Others: Principals’ vs. Agents’ Preferences

We study the degree to which financial investment advice is driven by the client's preferences, versus the preferences and incentives of the advisor. In a typical financial advice setting, clients can communicate their preferred investment profile to their financial advisor. We observe a high willingness of advisors to follow their clients’ preferred investment profiles, but also replicate evidence that advisor preferences also matter for investment choices. However, even though advisors are willing to follow their clients’ preferences, they often fail to do so from their clients’ perspective. This is because the investment profile terms often used in financial advice are very noisy in their perception and participants associate them with highly heterogeneous investments into risky assets. JEL: D14, D83, G11, G21
Behavioral Operations Management: A Review of the Field

Behavioral operations management (BOM) is one of the new areas in operations management. In the past 12 years, the field has made huge progress and researchers have become interested in this new perspective to solving operational problems. BOM is now one of the major subfields of operations management. In this paper, we examine and categorize areas of BOM based on the mainstream literature. Key areas include behavioral issues in new product development and project management, quality management, production management, inventory management, service operations, and forecasting. Studies in each area are divided into three subcategories, including OM context, individual attributes, heuristics, and biases, and individual differences. In OM context category, feedback and reward, training, work monitoring, teamwork and group decision making, goal setting, task assignment, and flexibility are among the main topics. In individual attributes, heuristics, and biases category, sunk cost effect and escalation of commitment, endowment effect, overprecision bias, planning fallacy, pull-to-center effect, anchoring and insufficient adjustment, and misperceptions of feedback are mainly discussed. In individual differences, analytic thinking and system thinking are mainly studied. New areas for research are suggested in each related section and are summarized in future directions and conclusion sections. In contexts such as new product development, project management, and inventory management, a shift to finding solution to performance improvement is beneficial instead of focusing on heuristics and biases and considering them as a deficiency in human decision making. Regarding individual differences category, a shift toward attributes other than cognitive abilities, such as global processing, creative thinking, and design thinking are recommended.
“ 3 D Object Reconstruction Using Kinect ”

Nowadays, a few low-cost devices support 3D acquisition. While 3D capture becomes a commonplace, decompose the object into its components is not an easy task. Segmentation can help address this problem by supplying data which may be used to identify object components. However, it might not give complete and accurate information about components. In a context where a digital repository with every component that can belong to physical objects is available, retrieval algorithms can allow robust reconstruction of a 3D model. Our work proposes a four phase solution to reconstruct 3D digitized objects, composed by previously registered components in a repository. We use Microsoft Kinect © to acquire 3D physical objects. A segmentation algorithm based on color information decomposes the object into a set of sub-parts. The component repository is queried using a shape-based retrieval algorithm, in order to identify which sub-part corresponds to each virtual component. Then, a 3D model of the physical object is reconstructed by assembling the retrieved components. Our approach has a wide application domain, ranging from entertainment to health or mechanical industry. To validate our proposal, we implemented and evaluated a toy-problem. We used LEGO © blocks, which can provide challenges similar to real-world applications. The results were encouraging and we believe that our approach is a very promising avenue for further work.
Study on Cost Estimation of Service Delivery in Cloud Computing Environment

The term cloud computing is sometimes used to refer to a new paradigm; some authors even cited a new technology that offers IT resources and services over the Internet. Cloud computing is becoming a powerful network architecture to perform large-scale and complex computing. Economic crisis can bring with enterprise as unpredicted business challenges now a days and more competition in the same market. To address different challenges, enterprise has to optimize and update their business operation. Moreover Cloud business is growing now days with respect to rapid application development with the existing large variety of options. So rapid advancements in cloud computing allowed multiple providers to offer basic computational resources to consumers as a digital service with the benefits of ‘ondemand’ and ‘pay-per-use’ characteristics of cloud. Basically Cloud Computing is an internet based distributed computing where user only concentrate on more on their business process rather than spending time the managing process. Here estimating cost is very important for cloud application when it needs remaining a certain services level at the same time interval. In this paper, we have studied some existing works on cost estimation of service delivery while application is being developed under Cloud computing environment.
Identifying conflicts of interest of reviewers using authors bibliometric networks

The process of peer review is a very important task that must be followed by a scientific document to be approved and then published in a scientific journal. Being such a delicate process, it is required that the elected reviewers guarantee the validity and quality of the submitted work, without influencing in its decision any type of link that may exist between the authors of a scientific document and the reviewers. However, many times this goes unnoticed and the reviewers are selected only according to their experience in a given field. This contribution proposes an approach to do recommendations based on the design of bibliometric networks such as: coauthorship networks, author co-citation networks and direct linkcitation networks. In this way, we seek to discover relationships between reviewers and authors of scientific documents in order to suggest appropriate reviewers, thus avoiding the recurring problem of conflicts of interest.
Developing Similarity Search Technology

Similarity searching has become more and more popular, which was stimulated by the growth of diverse data archives available on-line that offer search services to users, and by the increasing complexity of data that must be searched. This issue has also been recognized by major Internet search engines, exemplified by Google, that recently enriched their image search services by allowing users to search for images by similarity. They usually apply the following procedure. Firstly, a candidate set of images is obtained by a regular text search in images’ file names and associated textual tags. Then this set is reordered by images’ content, expressed as color histograms, for example. Finally, this result is presented to the user. In this thesis, we focus on similarity searching – content-based retrieval. In this area, data items are retrieved by their content rather than by textual information associated with them. For example, images are searched by comparing their color histograms to the histogram posed as a query by a user. The principle of ranking search results may also be applied to further increase the user’s satisfaction with the search results. The problem of similarity searching, as is studied in this thesis, uses metric space as a convenient data model. The author’s contributions range from centralized index structures via distributed ones up to a new indexing paradigm – self-organizing systems. These results represent the efficiency issue of similarity searching. On the other hand, the effectiveness of similarity searching can be expressed as efforts to model computerized similarity as closest as possible to the human perception of similarity. This problem is also tackled in this thesis by introducing a new query type. This thesis is conceived as a collection of articles. The collection contains 24 contributions published as either a monograph, chapters in monographs, or journal and conference papers. The author’s contribution is mainly in stating research issues and supervising students during solving the issues, but also by running some of experimental trials, collecting necessary input data, and writing and editing significant parts of articles. Concrete contributions to articles published are specified at the corresponding articles listed in sections titled “Articles in Collection”. In general, the author’s contribution is quantified as the ratio 1/x, where x is the number of authors of that particular article.
Pharmacognostical, phyotochemical and toxicity profile of flower of Ishwari - Aristolochia indica Linn.

Aristolochia indica Linn. (Aristolochiaceae) is popularly known as Ishwari and Nakuli in Samhitha Granthas. Ishwari is used in different forms for condition like sheethajwara, sarpavisha, vrana, ekangashopha, unmada, apasmara etc. One of methods of plant wealth conservation is by promoting use of plant parts other than root in therapeutics. Flower is one such plant part which can be studied as substitute for therapeutic benefits of root. Prior to such trials such proposed substitutes must undergo various pharmacognostical, analytical, toxicological and pharmacological studies. Microscopy, phtochemical examination, HPTLC and acute toxicity studies of A. indica flowers were performed flowing standard procedure. Powder microscopy revealed some specific characters for its identification. Phytochemical study showed presence of steroid, carbohydrate, flavonoids and saponins. HPTLC fingerprint of the flowers was derived. On toxicity evaluation no adverse effects were observed on administration of powder of flower orally in rat. These diagnostic features can be used as a fingerprint for the identification and differentiation of their substitute and adulterants of the plant. As there is no toxicity up to 2000 mg/kg body weight, 1/10 of the dose i.e. 200 mg/kg can be considered as therapeutic dose for further studies on this drug.
Synthesis Polymer Styrene Butadiene Hybrid Latex with Laponite Organoclay as Filler via Emulsion Polymerization Technique for Application in Paper Coating

Synthesis of styrene butadiene hybrid latex was performed via emulsion polymerization technique using various amount of laponite clay as filler. Laponite clay was modified with cationic surfactant methyl triphenylphosphonium bromide (MTPB) with ion exchange technique prior to polymerization process. The main objective of the modification is to render the surface of the clay layers to more organophilic. Emulsion polymerization was performed under semi batch process using 2 L laboratory stainless steel reactor with temperature 85°C to 90°C for 8 hours. Polymer hybrid styrene butadiene latex was characterized for its physical and chemical properties with standard ASTM Methods. Characterization of its binding and printing properties were carried out with standard testing method (TAPPI Methods) using single coating formulation on 80 gsm woodfree paper. Polymer hybrid latex based on styrene and butadiene monomers with laponite clay enhanced binding and printing properties of coated paper, addition of laponite clay to 6.0 wt % increased the binding resistance of the coated paper two times higher than pure latex. Reducing binder level become possible for cost saving.
PLANETARY BOUNDARY LAYER INVESTIGATION FROM LIDAR MEASUREMENTS OVER BUCHAREST

The Planetary Boundary Layer (PBL) heights have been calculated using the ratio of the two elastic channels, 1064 nm and 532 nm of a multiwavelength LIDAR system (RALI) located in Măgurele, near Bucharest, Romania, at the Romanian Atmospheric 3d Research Observatory. The measurements have been done continuouly between 09 and 12 July 2012. In this study we relied on the gradient method applied to the Range Corrected Signal (RCS). This method follows aerosols as tracers. The results from the three continuous days show the diurnal variation of the PBL above Măgurele. First day of the results shows an intrusion of long ranged transported aerosols mixed within the PBL. Also first day of measurements has the highest PBL at 2265 meters above sea level according to the highest air temperature 38 Celsius.
Effect of various compounding methods on acid red 18050- melamine modified urea formaldehyde resin compound as wood modifier

In order to simultaneously improve the strength and decoration properties of plantation wood, a multi-effect modifier was prepared by compounding acid red 18050(G) with melamine-modified urea formaldehyde resin (MUF). Various compounding methods for MUF synthesis such as adding dye with the first part urea (U1G) or with the second part urea (U2G), or direct blending with MUF resin (BG) were tested. Chinese fir plantation wood was impregnated with these modifiers separately, and its color, color fastness, and dyeing mechanism were studied. The results showed that G had good compatibility with MUF and could prolong its storage time, and all compound modifiers exhibited permeability and coloring effect on Chinese fir wood. Compared with G-dyed wood under the same conditions, all the compound dyed wood had better color fastness to water, and the U2G-dyed was the best, the color fastness to xenon light of U2G dyed wood was greatly improved. Fourier transform infra-red (FTIR) analysis showed that compared with MUF-modified wood, the dye affected MUF hydroxyl-methylation reaction in U1G, lowered the polycondensation degree, and extended its storage time. The dye might have promoted the ionic reaction between resin amino and dye sulfonic groups in U2G, thus displaying better color fastness.
Performance Evaluation of the Voltage Stability Indices in the Real Conditions of Power System

To prevent voltage collapse in the power systems, accurate estimates of the power system performance are necessary. In the previous studies only by adding reactive loads to weakest buses, the voltage stability of the power system lines are evaluated. Whereas in the real conditions of the power systems, the active and reactive loads are increased simultaneously and to provide actual prediction of lines voltage stability the effects of increasing both active and reactive loads should be considered. In this paper, the performance of some most important line voltage stability indices such as Lmn, FVSI, LQP and LCPI are evaluated in real conditions of the power system, and it is shown that the results of these indices are not identical. While that, these indices provide similar results as only reactive loads increased. In addition, to evaluate the obtained results, by using modal analysis method the lines that have most participation in voltage instability are detected. This study is investigated on the IEEE 14-bus test system.
Efficiency assessment of event-based predictive maintenance in Industry 4.0

Predictive maintenance has evolved from a vision to reality for several industries. Notwithstanding, there is not yet a clear view on the behavior of the algorithmic tools proposed. The aim of this work is to fill this gap and perform an insightful comparison and sensitivity analysis of the main representatives for event-based predictive maintenance, which typically rely on pattern mining and machine learning. We provide a publicly available environment to compare techniques and we perform extensive experiments. The results of our work show that fine tuning is required and judicious feature generation and selection are two important aspects in efficiently predicting faults.
VEGETABLES AS A SOURCE OF CAROTENOIDS

Plants are rich and still unexploited sources of bioactive compounds, attractive for their therapeutic properties and as the raw material for the formulation of pharmaceutical and food products. The colour of the plants, especially comestibles as vegetables or fruits, results from chemical compounds whose metabolic activity is the aim of many studies nowadays. The carotenoids, a group of organic compounds with an unsaturated skeleton of hydrocarbons, results in the colours of yellow, orange and red. Having antioxidant activity and, for some of them, being the precursors to vitamin A in the animal organisms are willingly used in very different medical applications. The article describes the current state of knowledge regarding the types and quantities of carotenoids in vegetables, the advancement of knowledge of their metabolic impact, their possible applications in medicine, as well as the desired directions for further research. Also, the scope of their industrial use and the prospects of carotenoids’ market development are included. This work is carried out in the framework of the COST Action – EUROCAROTEN CA15136, with the aim of the exchange and development of knowledge between European researchers working on carotenoids.
Application of Netflow logs in Analysis and Detection of DDoS Attacks 3 Methodology for Algorithm

The ability to detect DDoS attacks in the Internet backbone in real-time was crucial for network operators in order to provide an infrastructure of high quality. In this work, an algorithm for the near real-time detection of massive flooding attacks as well as TCP SYN flooding attacks has been developed and implemented as an UP Frame plug-in. The algorithm has been validated successfully by replaying Net Flow v5 logs of the SWITCH backbone border routers, containing known ICMP, UDP and TCP SYN flooding attacks from