Miracle-dz/UniFAR-FTUs huggingface dataset:
Ecological Health Assessment of Urban Ecosystem of Tianjin City

Urban ecological health assessment is the basis of making city planning, construction and management policy. Five elements were selected to build up an evaluation system, including vigor, organizational structure, resilience, and ecosystem service function and population health. Fuzzy comprehensive evaluation were employed to analyze and evaluate the healthy state of Tianjin urban ecosystem over 2008 to 2012 based on the method of mean-squared deviation to determine index weight. Results showed that the healthy status of Tianjin ecosystem was in sub-health level. The favorable factors affecting urban ecosystem healthy state of Tianjin included vigor, resilience and population healthy, while unfavorable factors included organizational structure and ecosystem service function. Main stress factors to healthy development are per capita water consumption, the amount of pesticide per hectare of arable land, per capital road area, urban population density and proportion of high-education people.
Optimization of Culture Medium for the Production and Partial Purification and Characterization of an Antibacterial Activity from Brevibacillus laterosporus Strain EA62

The present study was performed to report the bacterial identification, optimization of culture conditions and characterization of a novel antibiotic substance from a Bacillus sp. EA62 strain isolated from soil. The EA62 strain was identified based on 16S rRNA analysis. The new isolate EBD 9-1 showed 100% sequence identity with Brevibacillus laterosporus. The antibacterial activity of the new substance was examined against five pathogenic bacteria and was observed to be the most effective against Escherichia coli. An agar diffusion assay was performed to evaluate the antibacterial activity of the substance. The effects of some nutritional (amino acid, carbon, nitrogen and metal sources) and physical factors (pH and temperature) and incubation time on the antibiotic activity were studied. Antibiotic activity in basal medium reached the maximum levels after 72 h of incubation. The best antibiotic activity was obtained in the presence of glucose as a carbon source, yeast extract as a nitrogen source, glutamic acid as an amino acid source and MgSO4+CaCO3 as metal ion sources. For physical parameters, the best results were obtained at 37°C, pH 7.0. The antibiotic substance was partially purified, and the estimated molecular weight was 6.3 kDa. The minimum inhibitory concentration (MIC) values determined against five pathogen bacteria were >256 μg/ml. The substance was identified by thin-layer chromatography, and its Rf value was measured as 0.04 cm.
WEATHER BASED FOREWARNING MODELS FOR PESTS & DISEASES AND YIELD LOSS ASSESSMENT

In pests and diseases forewarning system, the variables of interest may be maximum pest population / disease severity, pest population / disease severity at most damaging stage of the crop, pest population / disease severity at different stages of crop growth or at various standard weeks, time of first appearance of pests / diseases, time of maximum pest population / disease severity, time of pest population / disease severity crossing threshold limit, extent of damage, weekly monitoring of pests and diseases progress, occurrence / non-occurrence of pests and diseases.
Main Application Protected Storage Library Protected Network Library Heap Heap Heap Thread Stacks Thread Stacks Thread Stacks Trampolines Trampolines Shared Buffers Domain Status Page Domain Status Page Domain Status

As network, I/O, accelerator, and NVM devices capable of a million operations per second make their way into data centers, the software stack managing such devices has been shifting from implementations within the operating system kernel to more specialized kernel-bypass approaches. While the in-kernel approach guarantees safety and provides resource multiplexing, it imposes too much overhead on microsecondscale tasks. Kernel-bypass approaches improve throughput substantially but sacrifice safety and complicate resource management: if applications are mutually distrusting, then either each application must have exclusive access to its own device or else the device itself must implement resource management. This paper shows how to attain both safety and performance via intra-process isolation for data plane libraries. We propose protected libraries as a new OS abstraction which provides separate user-level protection domains for different services (e.g., network and in-memory database), with performance approaching that of unprotected kernel bypass. We also show how this new feature can be utilized to enable sharing of data plane libraries across distrusting applications. Our proposed solution uses Intel’s memory protection keys (PKU) in a safe way to change the permissions associated with subsets of a single address space. In addition, it uses hardware watchpoints to delay asynchronous event delivery and to guarantee independent failure of applications sharing a protected library. We show that our approach can efficiently protect highthroughput in-memory databases and user-space network stacks. Our implementation allows up to 2.3 million library entrances per second per core, outperforming both kernellevel protection and two alternative implementations that use system calls and Intel’s VMFUNC switching of user-level address spaces, respectively.
NINE Using Rosetta for RNA homology modeling

The three-dimensional structures of RNA molecules provide rich and often critical information for understanding their functions, including how they recognize small molecule and protein partners. Computational modeling of RNA 3D structure is becoming increasingly accurate, particularly with the availability of growing numbers of template structures already solved experimentally and the development of sequence alignment and 3D modeling tools to take advantage of this database. For several recent “RNA puzzle” blind modeling challenges, we have successfully identified useful template structures and achieved accurate structure predictions through homology modeling tools developed in the Rosetta software suite. We describe our semi-automated methodology here and walk through two illustrative examples: an adenine riboswitch aptamer, modeled from a template guanine riboswitch structure, and a SAM I/IV riboswitch aptamer, modeled from a template SAM I riboswitch structure. Methods in Enzymology, Volume 623 # 2019 Elsevier Inc. ISSN 0076-6879 All rights reserved. https://doi.org/10.1016/bs.mie. 2019.05. 026 177
History of infertility relates to increased risk of gestational diabetes mellitus : a meta-analysis

Objective: History of infertility may be related to the development of gestational diabetes mellitus (GDM). However, studies investigating the relationship between history of infertility and GDM have yielded inconsistent findings. We performed a meta-analysis with all studies currently available to precisely estimate the association between history of infertility and GDM risk. Methods: The PubMed, Web of Science, Embase, China National Knowledge Infrastructure (CNKI), and Wanfang databases were searched for relevant articles published up to Sep. 1st, 2016 without language restriction. Relative ratios (RRs) with 95% confidence intervals (95% CIs) were calculated using STATA 12.0 software to evaluate the association of infertility and GDM risk. Results: Ten studies involving 430,715 subjects were included into our study. Overall, history of infertility was related to significantly increased risk of GDM (RR=1.90, 95% CI 1.50-2.40, P<0.001). Subgroup analyses by ethnicity and treatment of infertility further confirmed the findings. Sensitivity analysis showed that no single study materially influenced the pooled results in this meta-analysis. Conclusion: History of infertility may be a risk factor of GDM, particularly in patients receiving treatment for infertility.
Object-oriented analysis and design of graphic system of power system

Electric network figure is the foundation of power system analysis. On the basis of former research, the paper introduces the OOA model and design thoughs of the graphic system of power system, and elaborates the functions and features of graphic system.The graphic system was developed based on Visual C++ and Microsoft Access.Since adopting object-oriented analysis, the system is easy to be enlarged and maintained.
Optimal immunisation policies for epidemics

Policies of immunising the susceptibles in the general stochastic epidemic are considered. With costs assigned to the infection and immunisation of susceptibles, an optimal policy is found which at any stage minimises the expected future cost. Optimal policies are also found for the general deterministic epidemic and for an epidemic with carriers model. The three policies are compared and numerical examples are provided. An optimal policy is described in the situation when both isolation of infectives and immunisation of susceptibles are allowed.
ACQUIRING STATUS TREATMENT TECHNIQUES BY CREATING A LESSON PLAN

The Complex Instruction methodology is a pedagogical intervention that attempts to change the pupils' social class structure during group-work. These changes result in creating new roles for the teachers, as well as the pupils and increase cooperation between them. It results in the harmonious participation of the pupils in different status and improves completion of the task, i.e. the learning activities of small student groups. Our article aims to demonstrate how to prepare students for the technique of writing a lesson plan, how to achieve that they organize their lessons consciously, and how they can motivate and develop efficiently children with lower and higher capabilities. Preparation for the class is a cornerstone, whose tool was a lesson plan based on the Complex Instruction method. Wenglinsky's (2002) test results show that those schools performed better at the national competence testing (National Assessment of Educational Progress - NAEP), where teachers were prepared to work in a heterogeneous classroom and compile tasks that require multiple intelligence skills. He found that e.g. students who were more familiar in the chemical laboratories, had teachers who had received a more intensive practical training in the higher education institutions. The final conclusion of Wenglinsky's research is that those teachers will be the most successful in their work, who acquired both theoretical and practical knowledge during their teacher training. The teacher has to think over the execution of the tasks during preparation, and assess the possible barriers and the required tools for the solution of the task. Only those tasks should be selected that build on the pupils' already existing competencies, experiences and knowledge. It is worthwhile to apply different teaching techniques to raise attention and motivate. Various tools should be used to enrich the lesson, considering the pupils' needs (Hammerness et al., 2002). This study aims to examine how the teacher students' teaching competences can be developed by applying the Complex Instruction method in practice, which method is based on educating heterogeneous classes. The Complex Instruction method (Complex Instruction Program / CIP) is a teaching method which allows teachers to organize a high-level group work in classes where knowledge gap and expressing
Automatic Feature Engineering by Deep Reinforcement Learning Extended Abstract

We present a framework called Learning Automatic Feature Engineering Machine (LAFEM), which formalizes the Feature Engineering (FE) problem as an optimization problem over a Heterogeneous Transformation Graph (HTG). We propose a Deep Q-learning on HTG to support efficient learning of fine-grained and generalized FE policies that can transfer knowledge of engineering "good" features from a collection of datasets to other unseen datasets.
A Guided Multi-Scale Categorization of Plant Species in Natural Images

Automatic categorization of plant species in natural images is an important computer vision problem with numerous applications in agriculture and botany. The problem is particularly challenging due to the large number of plant species, the inter-species similarity, the large scale variations in natural images, and the lack of annotated data. In this paper, we present a guided multi-scale approach that segments the regions of interest (containing a plant) from a complex background of the natural image and systematically extracts scale-representative patches based on those regions. These multi-scale patches are used to train state-of-the-art Convolutional Neural Network (CNN) models that analyze a given plant image and determine its species. Focusing specifically on the identification of plant species in natural images, we show that the proposed approach is a very effective way of making deep learning models more robust to scale variations. We perform a comprehensive experimental evaluation of our proposed method over several CNN models. Our best result on the Inception-ResNet-v2 model achieves a top-1 classification accuracy of 89.21% for 100 plant species which represents a 5.4% increase over using random cropping to generate training data.
Tissue inhibitor matrix metalloproteinase 1 polymorphisms associated with colorectal cancer prognosis in a Han Chinese cohort

Purpose: Tissue inhibitor of metalloproteinase-1 (TIMP-1) is an inhibitor of matrix metalloproteinases, known to play a crucial role in tumorigenesis. It has significant predictive value for patients with colorectal cancer (CRC). However, its precise clinical applicability remains unknown. The current study investigated association between TIMP-1 gene polymorphisms and survival in CRC patients. Method: This study enrolled 118 endometrial cancer patients that underwent surgery for CRC between January 2011 and July 2015. Patients were genotyped for TIMP-1 polymorphism (rs4898, 372 T/C). In addition, TIMP-1 levels were assessed using enzyme-linked immunosorbent assay kits. Results: Higher plasma TIMP-1 levels were observed in patients with TIMP-1 rs4898 T allele, compared to patients with non-T alleles (P<0.001). There was significant association with vascular invasion (P=0.002), lymph node metastasis (P=0.038), distant metastasis (P=0.049), TNM stage (P=0.003), Dukes’ stage (P=0.045), and recurrence (P=0.005). Kaplan-Meier analysis demonstrated that TIMP-1 rs4898 T allele was associated with lower cumulative overall survival (OS) and recurrence-free survival (RFS) (P<0.001, P<0.001, respectively). Cox proportional hazards modeling showed the TIMP-1 rs4898 T allele to be an independent prognostic predictor for OS (HR=2.607, 95% CI=1.158-5.870, P=0.021) and RFS (HR=2.667, 95% CI=1.194-5.959, P=0.017) in CRC patients. Conclusion: TIMP-1 rs4898 polymorphisms are associated with unfavorable clinicopathological factors, indicating potential clinical predictive value for CRC patient prognosis.
13 Information-Processing Conceptualizations of Human Cognition : Past , Present , and Future

Historically, scholars have used contemporary machines as models of the mind. Today, much of what we know about human cognition is guided by a three-stage computer model. Sensory memory is attributed with the qualities of a computer buffer store in which individual inputs are briefly maintained until a meaningful entry is recognized. Short-term memory is equivalent to the working memory of a computer, being highly flexible yet having only a limited capacity. Finally, long-term memory resembles the auxiliary store of a computer, with a virtually unlimited capacity for a variety of information. Although the computer analogy provides a useful framework for describing much of the present research on human cognition, it is insufficient in several respects. For example, it does not adequately represent the distinction between conscious and non-conscious thought. As an alternative. a corporate metaphor of the mind is suggested as a possible vehiclefor guiding future research. Depicting the mind as a corporation accommodates many aspects of cognition including consciousness. In addition, by offering a more familiar framework, a corporate model is easily applied to subjective psychological experience as well as other real world phenomena.
COSTA: Composite Trust-Based Asset-Task Assignment in Mobile Ad Hoc Networks

In mobile ad hoc networks (MANETs), asset-task assignment problems have been explored with vastly different approaches. Considering the unique characteristics of MANET environments, such as no centralized trusted entity, a lack of resources, and high-security vulnerabilities, resource allocation is not a trivial problem particularly for situations where a mobile team aims to successfully complete a common mission. The existing approaches have studied asset-task assignment problems by best matching a node’s functionality and requirements of a given task. In this paper, we propose a task assignment protocol using the concept of multidimensional trust, namely, CompoSite Trust-based Assignment (COSTA), aiming to maximize the completion ratio of a common mission consisting of multiple tasks by balancing trust and risk in executing them. Based on the core concept of trust defined as the willingness to take the risk in performing a given task, COSTA selects qualified nodes for a given task while meeting an acceptable risk level for executing multiple tasks contributing to successful mission completion. Given a mission consisting of dynamic multiple tasks, we model each task with importance, urgency, and difficulty characteristics and use them for selecting qualified members. In addition, we model a node’s risk behavior (i.e., risk-seeking, risk-neutral, and risk-averse) and investigate its impact on mission performance where a payoff is given for member selection and task execution. We formulate an optimization problem for the task assignment using integer linear programming (ILP). Our simulation results validated with ILP solutions demonstrate the existence of an optimal acceptable risk level that best balances trust and risk so as to maximize the mission completion ratio. We conduct a comprehensive comparative analysis and show that COSTA achieves a higher mission completion ratio while incurring a lower communication overhead compared with non-trust-based counterparts.
European Seventh Framework Programme FP 7-218086-Collaborative Project Deliverable 2 . 7 Proposed algorithms for mission planning for groups of UAVs

AGH University of Science and Technology, AGH, Poland Gdansk University of Technology, GUT, Poland InnoTec DATA GmbH & Co. KG, INNOTEC, Germany IP Grenoble (Ensimag), INP, France MSWiA General Headquarters of Police (Polish Police), GHP, Poland Moviquity, MOVIQUITY, Spain Products and Systems of Information Technology, PSI, Germany Police Service of Northern Ireland, PSNI, United Kingdom Poznan University of Technology, PUT, Poland Universidad Carlos III de Madrid, UC3M, Spain Technical University of So a, TU-SOFIA, Bulgaria University of Wuppertal, BUW, Germany University of York, UoY, Great Britain Technical University of Ostrava, VSB, Czech Republic Technical University of Kosice, TUKE, Slovakia X-Art Pro Division G.m. b.H. , X-art, Austria Fachhochschule Technikum Wien, FHTW, Austria
Self-sufficient and self-contained sensing for local monitoring of in-site bridge structures

While conventional vibration-based monitoring provides an overall assessment of a bridge structure’s condition, it often fails in providing early warning for local damage. In this study, two separate sensor modules are developed for online tracking of post-tension (PT) tendon force loss and fatigue crack detection. An embeddable PT tendon force monitoring sensor, which periodically inspects the force level of the PT tendons inside a pre-stressed concrete (PSC) bridge, is developed based on eddy current measurement, and magnetic inductive coupling is used to transmit power and data between an external measurement system and the eddy current sensor embedded inside a PSC bridge. Next, a wireless fatigue crack detection sensor is developed to detect nonlinear ultrasonic modulation produced by a fatigue crack, and the sensor module is powered by a multi-mode energy harvester, which harnesses energy from sun light, low-frequency vibration and RF signals. Laboratory and field tests have demonstrated that the proposed techniques can detect a fatigue crack smaller than 100 m in width and about 40% loss of the initial PT tendon force.
Leaving Randomness to Nature : d-Dimensional Product Codes through the lens of Generalized-LDPC codes

Product codes (that are deterministic constructions) and Low-Density-Parity-Check (LDPC) codes (that come from a random ensemble of codes on graphs) have had little overlap in design and analysis methodology. We show that when nature offers suitable randomness in the form of the underlying statistical communications channel (e.g. discrete symmetric erasure and error channels), these two families of codes can be unified via their pruned residual Tanner graph post channel-corruption, allowing product codes to cross-leverage the design and analysis literature of LDPC codes. Further, for a subclass of these product codes, we can leverage the power of density evolution methods used successfully for LDPC codes. In this work, focusing on symmetric erasure channels, we show that d-dimensional product codes are isomorphic to a class of d-left regular Generalized Low-Density-Parity-Check (GLDPC) codes. This insight allows us to characterize the performance of d-dimensional product codes with component codes having constant erasure correcting capability, with relative simplicity using density evolution methods. The isomorphism also reveals that the choice of 3D product codes with a single parity-check per component offers superior performance at asymptotically high rates for the erasure channel to the predominantly-studied 2D product codes. Indeed, 3-dimensional product codes having a single parity check per component perform identically to 3-left-regular LDPC codes, which for the erasure channel (using density evolution methods) are about 22% away from Shannon capacity. This, combined with the simplicity and linear-time encoding and decoding of product codes, makes them attractive to a host of applications, with one particularly exciting one being their key role in performing coded distributed matrix multiplication [1] for straggler mitigation in modern large-scale distributed computing platforms.
EURECA 2013 – Biodiesel Production by Ethanolysis of Palm Oil with Immobilized Lipase Biodiesel Production by Ethanolysis of Palm Oil with Immobilized Lipase

Biodiesel synthesis by enzymatic ethanolysis of palm oil with Aspergillus oryzae lipase immobilized on ceramic honeycomb was studied. The effect of operating temperature, ethanol to oil molar ratio and water content on the reaction was experimental tested and compared to that of free lipase. The tested conditions were found to be at 45 °C, 3:1 and 5 % (v/v) respectively. Moreover, the conversion of fatty acid ethyl esters (FAEEs) using immobilized lipase through immersion pretreatment in palm oil increased by approximately 18%. Keywords— Fatty Acid Ethyl Esters, Ethanolysis, Palm Oil, Ceramic Honeycomb, Aspergillus oryzae lipase
AN AUTONOMOUS APPROACH TO WHEEL CHANGING PROBLEM

We describe a self-repairing robotic car capable of changing its wheels automatically. The robot is constructed from a Lego NXT kit and a Lynx Arm kit which are coordinated from a PC. The difficulty consists in assembling the wheel on its shaft with a high precision which is not possible with the Lego components. This was solved by creating an ensemble made from both wheel and its shaft. The entire ensemble is replaced instead of the wheel alone. We have performed several experiments which show the effectiveness of our approach.