Miracle-dz/UniFAR-FTUs huggingface dataset:
Cable Connection Scheme Optimization for Offshore Wind Farm Considering Wake Effect

In order to reduce the levelised cost of energy (LCOE) of the offshore wind farm, many optimization works should be done to reduce the investment and increase the energy production. As one of the main expenses, the electrical system can take up more than 15% of the total investment while cable costs take a large proportion. In order to make a cost-effective wind farm, the cable connection layout should be optimized. This paper proposes a novel way for offshore wind farm cable connection layout design. The LCOE, which concerns three aspects: electrical power losses, power captured by wind turbines (WT) and investment, is selected to set up the objective function. Since all the optimization variables are integers, a heuristic algorithm, integer particle swarm optimization algorithm (IPSO), is adopted to find a near optimal solution. To improve the performance of the IPSO, an adaptive method for parameter control is used to help to find a better solution. Comparisons are made with results obtained by the Norwegian center for offshore wind energy (NORCOWE) reference wind farm and the presented method. From the simulation, it can be noticed that the presented approach can help to find a cable connection scheme which can reduce the LCOE by 1.75%.
A Differentially Fed Transmission-Line-Excited Magnetoelectric Dipole Antenna Array for 5G Applications

A differentially driven transmission-line-excited magnetoelectric dipole (ME-dipole) is designed for fifth generation applications. The proposed antenna, realized using a single-layered printed circuit board with the plated-through-hole technology, is simple in configuration yet can achieve wide bandwidth and high gain. The antenna is composed of a $2 \times 2$ ME-dipole array surrounded by a rectangular cavity. A differential feed waveguide network based on an E-plane tee is also introduced to feed the prototype for measurements. Measurements show that the proposed antenna with the differential feed network can present an impedance bandwidth of 29.2% from 52.6 to 70.6 GHz with a broadside gain from 10.9 to 13.7 dBi. The proposed antenna retains all the salient features of ME-dipole in symmetric radiation patterns and relatively low cross-polarization and back radiation levels. The radiation patterns are mostly stable with the sidelobes that increase toward the higher end of the operating band.
Parallelizing Spectrally Regularized Kernel Algorithms

We consider a distributed learning approach in supervised learning for a large class of spectral regularization methods in an reproducing kernel Hilbert space (RKHS) framework. The data set of size n is partitioned into m = O ( n α ), α < 12 , disjoint subsamples. On each subsample, some spectral regularization method (belonging to a large class, including in particular Kernel Ridge Regression, L 2 -boosting and spectral cut-oﬀ) is applied. The regression function f is then estimated via simple averaging, leading to a substantial reduction in computation time. We show that minimax optimal rates of convergence are preserved if m grows suﬃciently slowly (corresponding to an upper bound for α ) as n → ∞ , depending on the smoothness assumptions on f and the intrinsic dimensionality. In spirit, the analysis relies on a classical bias/stochastic error analysis.
A Framework of Loose Travelling Companion Discovery from Human Trajectories

Through the availability of location-acquisition devices, huge volumes of spatio-temporal data recording the movement of people is provided. Discovery of the group of people who travel together can provide valuable knowledge to a variety of critical applications. Existing studies on this topic mainly focus on the movement of vehicles or animals with forcing the group members to stay always connected. However, the movement of people is different; people might belong to the same main group while they contribute in various sub-groups during their movement. In this paper, we propose a group pattern called loose travelling companion pattern (LTCP), which allows the members of a group to contribute to various sub-groups as long as the community of members does not change during the movement and all of the members stay connected for a few time-slots. In addition, we propose weakly continuous loose travelling companion pattern (WCLTCP) to relax the continuous time constraint in LTCP. Finally, three algorithms have been developed to discover the proposed group patterns: (i) straightforward approach, (ii) smart-and-fast method, and (iii) and opportunistic algorithm. Through the extensive experimental evaluation on both real and experimental datasets, the efficiency and effectiveness of the proposed group discovery approaches are proven.
Determination of some adsorption and kinetic parameters of α-amylase onto Cu+2-PHEMA beads embedded column

Abstract In order to investigate the biocatalytic properties of α-amylase on a composite cryogel matrix with immobilized metal affinity chromatography, Cu+2-attached poly(2-hydroxyethyl methacrylate) (Cu+2-PHEMA) beads, (2 µm size) were synthesized, then composite cryogel column was prepared by composing beads and PHEMA cryogels. After the preparation of Cu+2-PHEMA beads embedded cryogel column (Cu+2-BEC), some experiments were tested. Accordingly, the highest adsorption capacity (676.8 mg/g particles) of cryogels was achieved at acetate buffer of pH 5.0 with initial α-amylase concentration of 4 mg/mL. Immobilized enzyme has more stable pH range, between 6 and 7.5 than, the free one. Immobilization also increased the optimal activity from 25 to temperature range of 25–35 °C. Vmax and Km of α-amylase were detected as 1.149 U/mg protein, and 11.6 × 10−1 mM, respectively. α-Amylase was utilized 35 times repeatedly without losing the productivity.
High-quality Ellipse Detection Based on Arc-support Line Segments

Over the years many ellipse detection algorithms spring up and are studied broadly, while the critical issue of detecting ellipses accurately and efficiently in real-world images remains a challenge. In this paper, an accurate and efficient ellipse detector by arc-support line segments is proposed. The arc-support line segment simplifies the complicated expression of curves in an image while retains the general properties including convexity and polarity, which grounds the successful detection of ellipses. The arc-support groups are formed by iteratively and robustly linking the arc-support line segments that latently belong to a common ellipse at point statistics level. Afterward, two complementary approaches, namely, selecting the group with higher saliency to fit an ellipse, and searching all the valid paired arc-support groups, are utilized to generate the initial ellipse set, both locally and globally. In ellipse fitting step, a superposition principle for the fast ellipse fitting is developed to accelerate the process. Then, the ellipse candidates can be formulated by the hierarchical clustering of 5D parameter space of initial ellipse set. Finally, the salient ellipse candidates are selected as detections subject to the stringent and effective verification. Extensive experiments on three public datasets are implemented and our method achieves the best F-measure scores compared to the state-of-the-art methods.
State of the Art Optical Character Recognition of 19th Century Fraktur Scripts using Open Source Engines

In this paper we evaluate Optical Character Recognition (OCR) of 19th century Fraktur scripts without book-specific training using mixed models, i.e. models trained to recognize a variety of fonts and typesets from previously unseen sources. We describe the training process leading to strong mixed OCR models and compare them to freely available models of the popular open source engines OCRopus and Tesseract as well as the commercial state of the art system ABBYY. For evaluation, we use a varied collection of unseen data from books, journals, and a dictionary from the 19th century. The experiments show that training mixed models with real data is superior to training with synthetic data and that the novel OCR engine Calamari outperforms the other engines considerably, on average reducing ABBYYs character error rate (CER) by over 70%, resulting in an average CER below 1%.
Efficient and green aqueous−solid system for transphosphatidylation to produce phosphatidylhydroxybutyrate: Potential drugs for central nervous system's diseases

The synthesis of nonnatural phospholipid, phosphatidylhydroxybutyrate (PB), was firstly introduced by phospholipase D (PLD)‐mediated transphosphatidylation of phosphatidylcholine (PC) with sodium γ‐hydroxybutyrate (NaGHB) in the aqueous–solid system. Nanoscale silicon dioxide (NSD) was employed as a carrier to provide an “artificial interphase” between PC and PLD. Special attention has been paid to the effect of the PC coverage on the surface area of hybrids of NSD‐PC, the PC loading and the yield of PB. Results indicated that the highest PC loading of 98.3% and the highest PB yield of 97.3% were achieved. In addition, the free PLD in the aqueous–solid system showed the greater stability and pH tolerance than that in the traditional liquid–liquid system. The operational stability of free PLD solution was investigated. The yield of PB remained 70.7% after being used for five batches. The authors provide a new idea for drug design and the potential source of PB for medical experiments. PB is a potential drug and may have the excellent performance in the treatment of central nervous system's diseases. © 2018 American Institute of Chemical Engineers Biotechnol. Prog. , 35: e2726, 2019
Repeated domestication of melon (Cucumis melo) in Africa and Asia and a new close relative from India.

PREMISE OF THE STUDY The domestication history of melon is still unclear. An African or Asian origin has been suggested, but its closest wild relative was recently revealed to be an Australian species. The complicated taxonomic history of melon has resulted in additional confusion, with a high number of misidentified germplasm collections currently used by breeders and in genomics research. METHODS Using seven DNA regions sequenced for 90% of the genus and the major cultivar groups, we sort out described names and infer evolutionary origins and domestication centers. KEY RESULTS We found that modern melon cultivars go back to two lineages, which diverged ca. 2 million years ago. One is restricted to Asia (Cucumis melo subsp. melo), and the second, here described as C. melo subsp. meloides, is restricted to Africa. The Asian lineage has given rise to the widely commercialized cultivar groups and their market types, while the African lineage gave rise to cultivars still grown in the Sudanian region. We show that C. trigonus, an overlooked perennial and drought-tolerant species from India is among the closest living relatives of C. melo. CONCLUSIONS Melon was domesticated at least twice: in Africa and Asia. The African lineage and the Indian C. trigonus are exciting new resources for breeding of melons tolerant to climate change.
Architecture, technologies and challenges for cyber-physical systems in industry 4.0: a systematic mapping study

Background: The vision of a fourth industrial revolution lately strongly captured the attention of research A Cyber-physical system (CPS) is one of the main drivers of this vision. Such system controls an underlying factory interacting with sensors, actuators and other systems creating systems-of-systems. A main point of interest is how these components are built and interconnected, i.e. the system's architecture, and how it might be improved to increase reliability and security. Aims: Unfortunately, there is no review available describing and identifying recent research status and progress for such architectures. Thus, in this systematic mapping study, we overview research on architecture for CPS in the context of Industry 4.0. Method: With an initial automatic search and through iterative refining, first results were gathered. Next, forward and backwards snowballing was performed to integrate the results, giving a final population of 213 papers. The output of this study is firstly a categorization and plot of architectural styles. Secondly, the categorization is extended to include security concerns. Results: In general, there is a tendency in proposing solutions in the fields of system and software architecture while other areas are visibly under-researched. Most proposals focus in digital representation, information management and integration of solutions. Conclusions: While a lot of solution proposals for different architectures exist, there are many fields uncovered and most of the solutions still lack of validation and evaluation results. Our findings highlight areas for future research and provide suggestions for investigation approaches.
CHOPT : Automated Hyperparameter Optimization Framework for Cloud-Based Machine Learning Platforms

Many hyperparameter optimization (HyperOpt) methods assume restricted computing resources and mainly focus on enhancing performance. Here we propose a novel cloud-based HyperOpt (CHOPT) framework which can efficiently utilize shared computing resources while supporting various HyperOpt algorithms. We incorporate convenient web-based user interfaces, visualization, and analysis tools, enabling users to easily control optimization procedures and build up valuable insights with an iterative analysis procedure. Furthermore, our framework can be incorporated with any cloud platform, thus complementarily increasing the efficiency of conventional deep learning frameworks. We demonstrate applications of CHOPT with tasks such as image recognition and question-answering, showing that our framework can find hyperparameter configurations competitive with previous work. We also show CHOPT is capable of providing interesting observations through its analysing tools
Look, a guidance drone! Assessing the Social Acceptability of Companion Drones for Blind Travelers in Public Spaces

Using assistance technology always comes with the challenge of social acceptability. While an accessibility device might have great implications for a person with disabilities, it might come with unpleasant social implications. In this paper, we want to assess the social implications of flying companion quadcopters for navigating persons with visual impairments. We conducted an acceptability study with 15 sighted and 5 visually impaired participants and report on the results.
Internet Congestion Control via Deep Reinforcement Learning

We present and investigate a novel and timely application domain for deep reinforcement learning (RL): Internet congestion control. Congestion control is the core networking task of modulating traffic sources' data-transmission rates to efficiently utilize network capacity, and is the subject of extensive attention in light of the advent of Internet services such as live video, virtual reality, Internet-of-Things, and more. We show that casting congestion control as RL enables training deep network policies that capture intricate patterns in data traffic and network conditions, and leverage this to outperform the state-of-the-art. We also highlight significant challenges facing real-world adoption of RL-based congestion control, including fairness, safety, and generalization, which are not trivial to address within conventional RL formalism. To facilitate further research and reproducibility of our results, we present a test suite for RL-guided congestion control based on the OpenAI Gym interface.
Applying pattern-driven maintenance: a method to prevent latent unhandled exceptions in web applications

Background: Unhandled exceptions affect the reliability of web applications. Several studies have measured the reliability of web applications in use against unhandled exceptions, showing a recurrence of the problem during the maintenance phase. Detecting latent unhandled exceptions automatically is difficult and application-specific. Hence, general approaches to deal with defects in web applications do not treat unhandled exceptions appropriately. Aims: To design and evaluate a method that can support finding, correcting, and preventing unhandled exceptions in web applications. Method: We applied the design science engineering cycle to design a method called Pattern-Driven Maintenance (PDM). PDM relies on identifying defect patterns based on application server logs and producing static analysis rules that can be used for prevention. We applied PDM to two industrial web applications involving different companies and technologies, measuring the reliability improvement and the precision of the produced static analysis rules. Results: In both cases, our approach allowed identifying defect patterns and finding latent unhandled exceptions to be fixed in the source code, enabling to completely eliminate the pattern-related failures and improving the application reliability. The static analysis rules produced by PDM achieved a precision of 59-68% in the first application and 89-100% in the second, where lessons learnt from the first evaluation were addressed. Conclusions: The results strengthen our confidence that PDM can help maintainers to improve the reliability for unhandled exceptions in other existing web applications.
Differential Expression of Human Peripheral Mononuclear Cells Phenotype Markers in Type 2 Diabetic Patients and Type 2 Diabetic Patients on Metformin

Background: Although peripheral blood mononuclear cells (PBMC) have been demonstrated to be in a pro-inflammatory state in obesity and type 2 Diabetes Mellitus (T2DM), characterization of circulating PBMC phenotypes in the obese and T2DM and the effect of Metformin on these phenotypes in humans is still ill-defined and remains to be determined. Methods: Thirty normal healthy adult volunteers of normal weight, 30 obese subjects, 20 obese newly diagnosed diabetics and 30 obese diabetics on Metformin were recruited for the study. Fasting blood samples were collected and PBMC were isolated from whole blood. Polarization markers (CD86, IL-6, TNFα, iNOS, CD36, CD11c, CD169, CD206, CD163, CD68, CD11b, CD16, and CD14) were measured by RT-qPCR. Gene expression fold changes were calculated using the 2−ΔΔCT method for RT-qPCR. Results: Obesity and T2DM are associated an increased CD68 marker in PBMC. mRNA expression of CD11b, CD11c, CD169, and CD163 were significantly reduced in PBMC from T2DM subjects whereas CD11c was significantly inhibited in PBMC from obese subjects. On the other hand, macrophage M1-like phenotype was observed in T2DM circulation as demonstrated by increased mRNA expression of CD16, IL-6, iNOS, TNFα, and CD36. There were no significant changes in CD14 and CD86 in the obese and T2DM when compared to the lean subjects. Metformin treatment in T2DM reverted CD11c, CD169, IL-6, iNOS, TNFα, and CD36 to levels comparable to lean subjects. CD206 mRNA expression was significantly upregulated in PBMC of T2DM while Metformin treatment inhibited CD206 expression levels. Conclusions: These data support the notion that PBMC in circulation in T2DM express different pattern of phenotypic markers than the patterns typically present in M1 and M2 like cells. These phenotypic markers could be representative of metabolically activated macrophages (MMe)-like cells. Metformin, on the other hand, reduces MMe-like cells in circulation.
Use of Soil and Litter Ants (Hymenoptera: Formicidae) as Biological Indicators of Soil Quality Under Different Land Uses in Southern Rwanda

Abstract The use of soil and litter arthropods as biological indicators is a way to assess environmental changes, where ant species in particular may serve as important indicators of soil quality. This study aimed at relating the abundance of soil and litter ant species to soil parameters under different tree species, both native and exotic, and varieties of coffee and banana plantations. Variations were found in soil physicochemical parameters. A total of 30 species belonging to 14 genera, and four subfamilies, the Formicinae, Dorylinae, Myrmicinae, and Ponerinae were identified. Higher abundance was found in coffee plantations compared to banana plantations, exotic and native tree species. Species of Camponotus cinctellus and Odontomachus troglodytes occurred in all land uses which is a sign of tolerance to a wide range of soil properties. In addition, these species, together with Myrmicaria SP02, Phrynoponera gabonensis, Camponotus SP06, Myrmicaria opaciventris, Pheidole SP03, Tetramorium simillimum, Pheidole SP01, and Tetramorium laevithorax were not strongly correlated with soil physicochemical parameters. Species of Pheidole SP02 and Camponotus SP05 were restricted to specific soil physicochemical properties, while species of Tetramorium zonacaciae and Bothroponera talpa discriminated between native tree species, coffee plantations, soil organic carbon, sandy soil texture, and aggregate stability. We concluded that these ant species can differently indicate the soil quality depending on the land use. We recommended further studies in order to generalize these findings.
Molecular techniques reveal more secrets of fermented foods

Abstract Fermented foods were likely to have been the first among all types of processed foods consumed by human beings. The role that fermented food plays is not only related to the development of civilizations and cultural relationships between countries but also related to the nutritional importance of its population. Of course, the early manufacturers of fermented foods didn’t take into account the advantages of modern sciences, because enzymes and microorganisms were discovered just 150-200 years ago. For that reason, we can conclude why the ancient fermentation techniques were known to philosophers and alchemists, but not to biologists. It demonstrated that the fermentation mechanisms involved many secrets still undiscovered. Recently, applications of molecular techniques for analyzing and study the fermented foods have been explored. In this review, we provide answers with a critical vision to many questions for understanding the role of molecular techniques to discover the secrets of fermented foods such as how to evaluate the traditional fermented foods? Why using molecular techniques to study the fermented foods not else? Is the future will carry to us a boom in molecular technologies contribute to the detection of more secrets of the fermented food?