Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating the Efficient Parameter Values of Different Neighborhood Search Techniques of Simulated Annealing in Forest Spatial Planning Problems

The performances of heuristic algorithms are highly dependent on the parameters used, and usually difficult to determine subjectively. Thus, how to balance the relations between the qualities of the solutions and the values of the parameters has been a hot and lasting topic in the field of optimization research. This article presented a statistical method to estimate the efficient parameter values of three alternative neighborhood search techniques of simulated annealing when applied to forest spatial harvest scheduling problems, as an example. The neighborhood search techniques included: the conventional version of simulated annealing (Method1), and the swapping version (Method2) and the changing version (Method3) of 2-element optimization (2-opt) moves. Results indicated that the performances of different neighborhood search strategies highly depended on the problem size, in which the superiorities of Method2 increased from about 10% for smaller cases (400 units) to approximately 80% of larger cases (>3600 units) when compared the objective function values with Method1 and Method3. The efficient parameter values of the cooling rate (<italic>CR</italic>), the number of iterations per temperature (<italic>Ntem</italic>), and the number of iterations used for generating initial solution (<italic>Nsol</italic>) could be estimated using polynomial functions with the number of units, while the initial temperature (<italic>IT</italic>) should be estimated using exponential function, where the determination coefficient (<inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula>) of the fitted functions were all larger than 0.60 [except for <italic>Nsol</italic> and <italic>CR</italic> of Mehod1 (<inline-formula> <tex-math notation="LaTeX">$R^{2}=0.32$ </tex-math></inline-formula> and 0.42), <italic>CR</italic> of Method2 (<inline-formula> <tex-math notation="LaTeX">$R^{2}=0.20$ </tex-math></inline-formula>)]. The number of satisfactory solutions all increased linearly (<inline-formula> <tex-math notation="LaTeX">$R^{2} > 0.85$ </tex-math></inline-formula>) with the number of units, while the solution efficiency decreased linearly (<inline-formula> <tex-math notation="LaTeX">$R^{2} > 0.30$ </tex-math></inline-formula>). The verifications of two extra grid datasets indicated that the parameter optimization methods were valid.
PROXIMATE COMPOSITION OF CLUPEIDAE AND ENGRAULIDAE INHABITING THENGAITHITTU ESTUARY PUDUCHERRY- SOUTH EAST COAST OF INDIA

Estuarine fish are commercially valuable species and easy to cultivate in coastal areas. The biochemical composition is the yard stick to measure and assess the nutritional quality of food sources. Consumption of marine and estuarine fish provides an inexpensive source of protein with a high biological value, essential mineral and vitamins. Clupeidae (Sardinellalongiceps, S. gibbosa, Nematalosanasus, Ilishamelastoma) and Engraulidae (Stolephorusindicus, S. commersonni, Thryssamystax and T. malabarica) are dominant in Thengaithittu estuary are examined for proximate composition for their nutritional value. The average moisture content ranged from 67 to 73% and the majority of the fishes had protein contents between 14 to 21%. T. mystax and S. commersonni had high protein content 21.3% and 19.2%. Lipid content varied widely from 2.4 to 6.3% with S. longiceps had high lipid content (6.3%). Ash content varied from 1.42% to 4.9% and carbohydrate from 0.8% in S. commersonni to 4.82% in N. nasus.
Performance Analysis of Adaptive Modulation for Millimeter Wave Cellular Systems

In cellular networks that exploit the millimeter wave bands, access points are expected to be densely deployed and to share limited radio resources. In such systems, the geometric distribution of the downlink signal-to-interference-plus-noise ratio (SINR) is affected by several random variables such as path loss, blockage, small scale channel fading, interferer density, antenna array orientation, and thermal noise. Therefore, using fixed modulation in such varying environments is inefficient as it degrades the spectral efficiency and/or increases the outage probability. To tackle this issue, the transmitter needs to adapt the modulation order to the link condition. In this paper, we introduce an adaptive modulation technique, which depends on the geometric distribution of the SINR, for millimeter wave cellular systems in order to enhance their performances in terms of average spectral efficiency. In this case, the transmitter adjusts the modulation type of the transmitted signal based on the receiver geometry and the link condition. First, we present an analytical model using geometry tools to compute the statistical distributions of the downlink SINR. Then, the performance of the adaptive modulation scheme is studied and evaluated in terms of the average spectral efficiency. Numerical results show that, while keeping the outage probability as minimum as possible, this geometry-based adaptive modulation can efficiently enhance the millimeter wave system average spectral efficiency.
En-route Multilateration System Based on ADS-B and TDOA/AOA for Flight Surveillance Systems

The traditional radar techniques are not suitable for the precise positioning of the aircraft with the rapid development of air traffic. Automatic dependent surveillance-broadcast (ADSB) is one of the most important technologies in the field of air traffic control. Unfortunately, the ADS-B technique is prone to cyber threats due to its open architecture. In order to validate the ADS-B signal and to enhance positioning accuracy of en-route aircraft, an approach unite the technology of ADS-B and multilateration (MLAT) is presented, where a dynamic flight model of aircraft is utilized. We use MLAT to overcome the problems caused by the drawbacks of ADS-B. Moreover, we propose a hybrid time-difference-of-arrival/angle-of-arrival (TDOA/AOA) positioning technology using Extened Kalman Filters (EKF) for ADS-B/MLAT positioning system. The experimental results show that the hybrid technology can improve the position accuracy and enhance the robustness of the surveillance systems.
When measurements fail: using an interactive SLAM solution to fight bad odometry

In this paper we use the underlying pose graph structure of graph SLAM to allow the user to inspect and intervene into the Simultaneous Localization and Mapping (SLAM) process. With post-processing the map by inserting custom constraints into the optimization problem, the user can improve the quality of the map obtained as the final SLAM result. We refer to this inspection and intervention process as interactive SLAM. The mathematical background, which allows such interventions, is laid out, and a software implementation is used to improve the quality of a map created at the Faculty of Electrical Engineering and Computing, University of Zagreb.
Prerequisites for the Adoption of the X - Road Interoperability and Data Exchange Framework: A Comparative Study

Data Exchange layer X-Road successfully implemented in Estonia is a key enabler for secure data exchange and interoperability in public and private sector. Other countries are adopting the similar interoperability and data exchange framework as a part of e-governance solution. To ensure successful adoption of previously named framework it is important to identify crucial prerequisites influencing the process. In current paper, we analyse the practice of nine different countries. First, we define possible prerequisites in combination with relevant literature, data and documentation analysis. Second, we validate these prerequisites through qualitative expert interviews and identify additional prerequisites. The focus of this paper is on X-Road adoption critical prerequisites, in this context we analyse X-Road deployment wealth indicators, the impact of prerequisites in accelerating X-Road implementation, and procedures to assess countries readiness to adopt X-Road. Research results presented in this paper offer initial assessment framework to investigate the country's readiness to adopt systems similar to X-Road.
Trap Dynamics Model Explaining the RON Stress/Recovery Behavior in Carbon-Doped Power AlGaN/GaN MOS-HEMTs

In this paper, we present simulation results that reproduce stress and recovery experiments in Carbon-doped power GaN MOS-HEMTs and explain the associated RON increase and decrease as the result of the emission, redistribution and re-trapping of holes within the Carbon-doped buffer. The proposed model can straightforwardly clarify the beneficial impact of the recently proposed p-type drain contact on RON degradation as being a consequence of enhanced hole trapping and reduced negative trapped charge within the buffer during stress.
Analysis of gene regulatory networks in Pyrococcus furiosus by ChIP-seq

Transcription in Archaea relies on a eukaryotic-like transcription machinery composed of general transcription factors, the RNAP and corresponding promoter elements. In contrast, the regulation of archaeal gene expression depends on bacterial-like transcription factors. In the present work the gene regulatory networks of several archaeal transcription factors from the hyperthermophilic euryarchaeon P. furiosus were examined by ChIP. Moreover, combining ChIP with high-throughput sequencing (ChIP-seq) enabled the first time genome-wide TF binding site mapping in P. furiosus. ChIP-seq revealed that the global regulator of sugar metabolism in P. furiosus, TrmBL1, not only represses and activates expression of sugar-uptake-, glycolysis- and gluconeogenesis-specific-enzymes encoding genes as proposed, but it also controls transcription of genes encoding proteins catalyzing proteolysis, AA metabolism and nucleotide degradation. In addition, TrmBL1 indirectly affects expression of genes involved in functionally-linked metabolic pathways by transcriptional repression of the hitherto not well-characterized secondary transcription factor PF1476. In contrast, the anti-TrmB antibodies were not specific enough to allow investigation of the proposed co-regulation of TrmB and TrmBL1 in sugar metabolism. Furthermore, the genes encoding TrmB and the TM-system were deleted in the P. furiosus type strain. After successfull establishment of the ChIP-seq approach, genome-wide TF binding site mapping was extended to analyze a third paralogous TrmB protein designated as TrmBL2. These studies uncovered numerous potential functions of the TF as both architectural abundant DNA binding protein and global transcriptional regulator in P. furiosus. Furthermore, TrmBL2 ChIP-seq analysis using P. furiosus cells incubated at 107° for 30 min revealed a novel unexpected role of the protein in the heat shock response. TFB-RF1 functions as transcriptional activator by recruitment of TFB to an imperfect BRE. Under optimal growth conditions expression of TFB-RF1 is not detectable and the transcription factor had to be over expressed from the fbpase promoter. First combination of ChIP-seq with the recently developed in vivo over-expression system of P. furiosus confirmed binding of the TF to its in vitro designated binding site in vivo. However, no additional binding sites were identified, which would elucidate a physiological function as regulator. The presented studies of this work contribute to a better understanding of the mechanisms of transcriptional control mediated by gene regulatory networks to achieve optimal growth of the cells in response to differing environmental as well as intracellular conditions.
Deep Guidance Network for Biomedical Image Segmentation

Segmentation of 2D images is a fundamental problem for biomedical image analysis. The most widely used architecture for biomedical image segmentation is U-Net. U-Net introduces skip-connections to restore the spatial information loss caused by down-sampling operations. However, for some tasks such as the retinal vessel segmentation, the loss information of structure can not be fully recovered since the vessels is merely a curve line that can not be detected after several convolutions. In this paper, we introduce a deep guidance network to segment the biomedical image. Our proposed network consists of a guided image filter module to restore the structure information through the guidance image. Our method enables end to end training and fast inference (43ms for one image). We conduct extensive experiments for the task of vessel segmentation and optic disc and cup segmentation. The experiments on four publicly available datasets: ORIGA, REFUGE, DRIVE, and CHASEDB1 verify the effectiveness of our method.
Hyperspectral Image Classification via Exploring Spectral–Spatial Information of Saliency Profiles

Morphological features have shown promising performances for hyperspectral image (HSIs) classification, as they can efficiently extract the multilevel spatial information of HSIs. However, the objects in the scenes are always with different sizes and shapes, making it difficult to excavate spatial information of important structures completely by the existing morphological methods. To address this problem, we propose a novel two-stage framework based on morphology and superpixel. Specifically, we propose self-dual saliency profiles (SPs) based on a saliency measure considering the grayscale contrast within objects and edge information. SPs are hierarchical features that characterize spatial information for salient objects whose saliency index is the significant local maxima. The SPs are constructed based on a two-step algorithm. First, all salient objects of different shapes in the scene are preserved, and the undesired spatial details are discarded by attribute filters based on the saliency measure. Second, the morphological feature is generated based on the organization structure of salient objects in the scene, which provides hierarchical spatial features of the image. Then, the superpixel segmentation is performed on each of the extracted SPs on the basis of the spatial information of salient objects. And, two types of superpixel-based features are extracted from SPs to exploit the information in SPs. The extracted innersuperpixel and intersuperpixel features are fused with spectral information to produce the classification map. The experiments conducted on three HSIs show that, the proposed approach significantly outperforms the other state-of-the-art methods.
Functional and Molecular Characterization of a Monoclonal Antibody against the 165–186 Peptide of Human 1β

A synthetic peptide of human recombinant interleukin 1β (hrIL‐1β) 165–186, which exhibits biological activity in the human fibroblast assay, was used as an immunizing antigen to obtain a murine monoclonal antibody (MoAb) termed FIB 1 This MoAb, an IgG1, reacts specifically with hrIL‐1β. but not with hrIL‐1α, as measured in enzyme‐linked immunosorbent assays (ELISA). The MoAb FIB 1 detects the characteristic 17 kDa IL‐1 protein in Western blots. Binding to the antigen is specific, as deduced also from the close correlation of ELISA immunoreactivity with IL‐1 biological activity. The anti‐IL‐1β 165–186 Ab specifically neutralizes the biological activity of hrIL‐1β and native IL‐1, as measured by the IL‐1‐induced proliferation of murine thymocytes and human fibroblasts and the IL‐1‐dependent IL‐2 production by murine T cells (EL4‐6.1). Fifty per cent of hrIL‐1β activity (25 U/ml, or 0.25 ng/ml) has neutralized by less than 30μg/ml of MoAb. Furthermore, FIB 1 recognizes intracellular IL‐1 in lipopolysaccharide‐stimulated human peripheral blood mononuclear cells. The anti‐IL‐1β 165–186 Ab does not react with the shorter IL‐1β fragment 161–173 in solid‐phase ELISA, therefore the binding region seems to be localized in the amino acid sequence VALGLKEKN‐LYLS. A sandwich‐ELISA, using a polyclonal sheep anti‐IL‐1β 251–269 Ab as the capture antibody and anti‐1β‐165–186 MoAb as the detecting probe, allowed the determination of IL‐1β from crude culture supernatants.
Single Node Detection on Direction of Approach

While unmanned aerial vehicles (UAVs) present us with many benefits in the modern world, the immature use and malicious exploitation of this technology increase its potential to cause harm and fear. For that reason, in order to mitigate threats, the demand for technology that enables the detection of UAVs is ever increasing. Many studies focus on detecting the presence of UAVs and the direction of approach (DOA), but in order to overcome the issues caused by acoustic sensor limitations, researchers used a combination of sensors and nodes. This paper proposes a different method to overcome the limitation with a single node in place of the previous approach of using multiple and high-priced acoustic sensors. Within this study, data augmentation and Mel-frequency cepstral coefficients (MFCCs) were used in the dataset. We investigated convolutional neural network (CNN), convolutional recurrent neural network (CRNN) and ResNet-50 to identify UAV’s DOA on a Raspberry Pi 3 which has low computational resources. Our empirical results confirm that the CRNN classifier is more suited to operate in a real detection system since it can predict DOA in only 0.429 seconds with an accuracy of 97.60% on a Raspberry Pi 3.
Open innovation and the value of crowds: implications for the fashion industry

Firms in many industries are seeking to incorporate ideas from outside parties to complement their own internal resources and capabilities. Suppliers, distributors, end users, scientists, firms in unrelated industries and even competitors can be important sources of information and ideas. Furthermore, with the computing capabilities available today, firms can scan online communities for sources of ideas and even harness the ideas generated by a select few key users with insights into emerging mainstream customer needs. All of this additional input helps firms compete profitably in an increasingly difficult environment. New trends include open innovation, crowdsourcing, user toolkits, mass customization and lead-user analysis. While there is emerging academic research on all of these topics, their usefulness in fashion marketing and merchandising remains relatively unexplored. This is potentially a great research opportunity, as fashion designers can obtain key ideas that boost competitiveness by working more closely with customers, suppliers, retailers and other parties. This article presents the state of the art in each of these trends, and concludes with a discussion of the implications for fashion marketing and merchandising academic research and practice.
An IEEE 1451 Vehicular Sensor Network Development

The mobility platform proposed is based on e-bikes and a set of charging stations, spread all over the city, that use the sun's energy to charge the batteries of e-bikes. At the same time, the mobility of e-bikes is used to collect environmental parameters related to air quality. The user's mobile phone is used to connect the e-bike to the traceability and data collection system. The merge of technologies such as IoT and Sensor Networks (SN) in vehicles have originated the concept of Vehicular SN (VSN). To promote the acceptance and implementation of standardized SNs, the objective of the present work is to present a VSN compliant with the IEEE 1451 family of standards. It is presented the overall architecture of the VSN and is it described the implementation of services, methods and group of transducers to achieve the expected smartness of a VSN. Also, will be underlined how all VSN components interoperate as well as what operations should be done by which component in order to reduce energy
Eff icacy of angler catch data as a population and conservation monitoring tool for the f lagship Mahseer f ishes (Tor spp.) of Southern India

Mahseer (Tor spp.) are flagship fishes in South Asian rivers. Their populations are threatened through poaching and habitat disturbance, yet they are highly prized game fishes due to their large size, appearance and sporting qualities. The international recreational angling community has frequently been cited as playing a vital role in conserving these fishes while also providing economic benefit to poor rural communities. Owing to a lack of scientific data and the considerable challenges associated with monitoring fish populations in large monsoonal rivers, efforts to determine the long-term trends in their populations has focused on sport-fishing catch records. Here, catch data collected between 1998 and 2012 from Galibore, a former fishing camp on the River Cauvery, Karnataka, India, were analysed to determine the catch per unit effort (CPUE – by number and weight) as an indicator of relative fish abundance, along with the size structure of catches. This fishery operated a mandatory catch-and-release (C&R) policy, and provided the fish community with protection from illegal fishing. Between 1998 and 2012, 23 620 hours fishing effort were applied to catch and release 6161 mahseer, ranging in size from 1 to 104 lbs (0.45–46.8 kg) in weight. Across the period, CPUE in number increased significantly over time with a concomitant decrease in CPUE by weight, revealing strong recruitment in the population and a shift in population size structure. This suggests a strong response to the C&R policy and the reduction in illegal fishing, indicating that conservation strategies focusing on the beneficial and negative aspects of exploitation can be successful in achieving positive outcomes. These outputs from angler catch data provide insights into the mahseer population that were impossible to collect by any alternative method. They provide the most comprehensive analysis of a long-term dataset specific to any of the mahseer species across their entire geographical range and demonstrate the value of organised angling as a conservation monitoring tool to enhance biological data, and inform conservation and fishery management actions. Copyright © 2014 John Wiley & Sons, Ltd.