Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Learning Approaches to Classification of Production Technology for 19th Century Books

Cultural research is dedicated to understanding the processes of knowledge dissemination and the social and technological practices in the book industry. Research on children books in the 19th century can be supported by computer systems. Specifically, the advances in digital image processing seem to offer great opportunities for analyzing and quantifying the visual components in the books. The production technology for illustrations in books in the 19th century was characterized by a shift from wood or copper engraving to lithography. We report classification experiments which intend to classify images based on the production technology. For a classification task that is also difficult for humans, the classification quality reaches only around 70%. We analyze some further error sources and identify reasons for the low performance.
Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations (discussion paper)

This study was supported by the National Basic Research Programme (973 programme) of China (Grant No. 2013CB036400). The first author grate- 10 fully acknowledges the financial support provided by the China Scholarship Council. The APHRODITE data were downloaded from http://www.chikyu. ac.jp/precip/products/index.html. The TRMM3B42 data are downloaded from http://mirador.gsfc. nasa.gov/cgi-bin/mirador/ presentNavigation.pl? tree=project&project=TRMM&dataGroup=Gridded. TRMM3B42RT data are downloaded from ftp://trmmopen.nascom. nasa.gov/pub/merged/mergeIRMicro/. PER- 15 SIANN data are downloaded from http://chrs.web. uci.edu/persiann/data.html. GSMAP-MVK+ data are downloaded from http://sharaku.eorc. jaxa.jp/GSMaP_crest/. The GLDAS data are downloaded from http://mirador.gsfc. nasa.gov/cgi-bin/mirador/homepageAlt.pl? keyword= GLDAS_NOAH025SUBP_3H. The data of Biliu basin were obtained from the Biliu reservoir administration.
Ballistic transport of long wavelength phonons and thermal conductivity accumulation in nanograined silicon-germanium alloys

Computationally efficient modeling of the thermal conductivity of materials is crucial to thorough experimental planning and theoretical understanding of thermal properties. We present a modeling approach in this work that utilizes frequency-dependent effective medium to calculate lattice thermal conductivity of nanostructured solids. The method accurately predicts a significant reduction in the thermal conductivity of nanostructured Si80Ge20 systems, along with previous reported thermal conductivities in nanowires and nanoparticles-in-matrix materials. We use our model to gain insight into the role of long wavelength phonons on the thermal conductivity of nanograined silicon-germanium alloys. Through thermal conductivity accumulation calculations with our modified effective medium model, we show that phonons with wavelengths much greater than the average grain size will not be impacted by grain boundary scattering, counter to the traditionally assumed notion that grain boundaries in solids will act as diffusive interfaces that will limit long wavelength phonon transport. This is further supported through a modulation frequency dependent thermal conductivity as measured with time-domain thermoreflectance.
Global Illumination in Participating Media

This report provides a survey of several state-of-the-art algorithms to render global illumination in participating media. Photon mapping, radiance estimation methods, virtual light methods and a technique to model photon density using Gaussian mixtures are described. The description of the algorithms focuses on giving a brief overview of the radiance evaluation and properties like biased or unbiased, handling heterogeneous media and anisotropic scattering. CR Categories: I.3. 7 [Computer Graphics]: Three-Dimensional Graphics and Realism—Raytracing
Lidar-observed enhancement of aerosols in the upper troposphere and lower stratosphere over the Tibetan Plateau induced by the Nabro volcano eruption

Abstract. Vertical profiles of aerosol extinction coefficients were measured by a micro-pulse lidar at Naqu (31.5° N, 92.1° E; 4508 m a.m.s.l.), a meteorological station located on the central part of the Tibetan Plateau during summer 2011. Observations show a persistent maximum in aerosol extinction coefficients in the upper troposphere–lower stratosphere (UTLS). These aerosol layers were generally located at an altitude of 18–19 km a.m.s.l. , 1–2 km higher than the tropopause, with broad layer depth ranging approximately 3–4 km and scattering ratio of 4–9. Daily averaged aerosol optical depths (AODs) of the enhanced aerosol layers in UTLS over the Tibetan Plateau varied from 0.007 to 0.030, in agreement with globally averaged levels of 0.018 ± 0.009 at 532 nm from previous observations, but the percentage contributions of the enhanced aerosol layers to the total AOD over the Tibetan Plateau are higher than those observed elsewhere. The aerosol layers in UTLS wore off gradually with the reducing intensity of the Asian monsoon over the Tibetan Plateau at the end of August. The eruption of Nabro volcano on 13 June 2011 is considered an important factor to explain the enhancement of tropopause aerosols observed this summer over the Tibetan Plateau.
A fast approach for integrating ORB descriptors in the bag of words model

In this paper we propose to integrate the recently introduces ORB descriptors in the currently favored approach for image classification, that is the Bag of Words model. In particular the problem to be solved is to provide a clustering method able to deal with the binary string nature of the ORB descriptors. We suggest to use a k-means like approach, called k-majority, substituting Euclidean distance with Hamming distance and majority selected vector as the new cluster center. Results combining this new approach with other features are provided over the ImageCLEF 2011 dataset.
Design of Enterprise Social Media: Recommendations from a Case Study

Enterprise social media (ESM), such as wikis, blogs, or social networks, have rapidly spread across organisations. They offer unique means to support knowledge management, knowledge creation, or internal communication, especially in distributed work environments. While most work focuses on what ESM can be used for, there is little research so far on how ESM themselves should be further developed. Based on the results of a case study at a German enterprise, we come up with recommendations for designers who seek to support the development of ESM.
Molecular Characterization and Phylogeny Based Analysis of Intron I Sequence of Myostatin (MSTN) Gene in Iranian Makuei Sheep Breed

Abstract Myostatin (MSTN), a negative regulator of skeletal muscle development, acts as a potential candidate gene used to increase muscle mass. Likewise, sheep MSTN gene has an important role in meat production. MSTN is made up of 376 amino acids, and is synthesized as a precursor protein. To investigate the MSTN in Iranian native Makuei sheep, a polymerase chain reaction-single strand conformational polymorphism (PCR-SSCP) analysis was used. Genomic DNA was isolated from the blood samples. A 417-bp of MSTN intron I segment was amplified using locus-specific primers. Four SSCP patterns were identified and nucleotide sequencing of the Makuei sheep MSTN gene was done and registered in the NCBI GenBank with “KJ526625” number. Three novel single nucleotide polymorphisms (SNPs) were found in the samples. These SNPs are found in 224bp, 226bp and 242bp locations. Accordingly three substitutions (c.224C>T; c.226A>G; c.242G>T) were observed in the intron 1 region of MSTN gene. The effects of the observed SNPs on breeding values of some biometric traits were investigated and the substitution of c.226A>G was found to be associated with heart girth (HG) and leg circumference (LC). Phylogenetic analysis, based on the nucleotide sequences indicated similar evaluation with the GenBank reference sequences. It seems that the observed polymorphisms of the ovine MSTN gene are associated with HG and LC traits.
An Approach for Malware Detection and Predictive Analysis Using Artificial Neural Networks

Malware Detection and Predictive Analysis is under research with escalating velocity from more than a decade still there is scope of research because of the increasing vulnerabilities on assorted media and network channels. From a long time, the monitoring of servers and forensic analysis of network infrastructure is done using packet capturing (PCAP) tools and intrusion detection systems (IDS). These activities are performed using PCAP and IDS tools available in the market which includes open source software as well as commercial products. This work underlines the assorted aspects of malware detection and avoidance approaches with the concluding remarks. In proposed work of this research, a unique and effective deep learning based approach is developed and implemented with the base of malware datasets to be fetched from real honeypots and honeynets. The proposed artificial neural net based multilayered approach is used for training and predictive analytics of malware on multiple parameters including error factor, accuracy rate and overall performance. In earlier approaches for malware detection and prior predictions, the density based clustering is used and related highest accuracy is achieved to 97%. Whereas in our proposed approach using ANN the maximum accuracy
Prior estimation of post accuracy

We introduce an algorithm to estimate the evolution of accuracy in part-of-speech tagging on the whole of a training corpus, based on the results obtained from a portion of the latter. The technique approximates iteratively the vallue that we seek in the position desired, independently of the statistical model and dataset used. The process proves to be formally correct with respect to our working specifications and includes a stable stopping criterion. This allows the user to fix a reliable convergence threshold with respect to the accuracy finally achievable. Our aim is to evaluate the training effort, supporting decision making in order to reduce the need for both human and computational resources during tagger generation. The proposal is of interest in at least three operational procedures. The first is the anticipation of accuracy gain, with the purpose of measuring how much work is needed to achieve a certain level of performance. The second relates the comparison between taggers at training time, with the objective of completing this task only for the tool that predictably better suits our requirements. The prediction of accuracy is also a valuable item of information for the customization of the tagger, for example to select the tag-set, since we can estimate in advance its impact on both the performance and the development costs. The experiments corroborate our initial expectations.
Cloning of Brnl , a biosynthesis reductase gene involved in melanin in Cochilobolus heterostrophus

Melanins are dark pigments, and their production is widespread in the fungal kingdom. The importance of melanins for the survival and longevity of fungal propagules has been recognized for a long time. The pathway of melanin biosynthesis is different among fungal groups (Bell and Wheeler, 1986). Some species of Ascomycotina and related Deuteromycotina produce dark-brown to black melanins from pentaketide via 1, 8-dihydroxynaphthalene (DHN) as the precursor of the polymer. This pathway was first studied in Verticillium dahliae Kleb. using melanin-deficient mutants (Bell et al., 1976). In other plant patho-
FRUIT AND STONE VARIABILITY IN THREE ARGAN ( ARGANIA SPINOSA ( L . ) SKEELS ) POPULATIONS

Little is known about morphological variability of argan (Argania spinosa (L.) Skeels), a multipurpose tree endemic to Morocco. During three following years, 11 fruit and stone characters (fruit color, fruit and stone weight, length, width and width 1 length ratio, flesh weight, and stone chambers number) were observed on 30 mature fruits collected from 30 trees within each of three populations in the major area of distribution of the specie, southwest of Morocco. The study established a high level of morphological variability. However, interpopulation (between population) contribution to total variance was lower than intra-population (treelpopulation or its interaction with year). The most discriminant criterion between populations were the least variable characters. Three clusters grouping the morphotypes were not related to geographical distribution, showing a lack of between population diversity. Values of repeatability (an estimate of broad sense heritability) varied between 52% and 8%. These were as high as 45% for characters of economic importance (i.e. fruit and stone weight), thus exhibiting variability to capture in an argan breeding program.
MICROWAVE REMOTE SENSING OF HYDROLOGY IN SOUTHERN AFRICA

ScanSAR systems such as ENVISATs ASAR Global Mode allow monitoring of dynamic processes at medium resolution. Hence they are especially useful for monitoring hydrologic processes such as soil moisture and inundation dynamics. In this paper we present two studies which investigate the capabilities of ScanSAR ASAR Global Mode (1 km resolution) on the southern African subcontinent. One study focuses on the monitoring of the Okavango delta, Botswana. Temporal and spatial dynamics for the year 2005 have been investigated on approximately monthly time steps. The second study, SHARE, aims at enabling an operational soil moisture monitoring service for the region of the Southern African Development Community (SADC) by using ASAR Global Mode data in combination with ERS/METOP scatterometer data to build a synergistic 1 km soil moisture product. In this study ASAR Global Mode data is used in two ways: First it is used directly to retrieve soil moisture information using a simple change detection algorithm; Secondly, a scaling layer is defined which allows enhanced interpretation of coarse resolution (25 km) scatterometer data.
Endotoxin Occurrence in Raw and Reclaimed Wastewater

Short Retraction Notice The paper does not meet the standards of "Journal of Water Resource and Protection". This article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retraction Guidelines. The aim is to promote the circulation of scientific research by offering an ideal research publication platform with due consideration of internationally accepted standards on publication ethics. The Editorial Board would like to extend its sincere apologies for any inconvenience this retraction may have caused. Editor guiding this retraction: Prof. Dr. Jian Shen (EiC of JWARP). The full retraction notice in PDF is preceding the original paper which is marked "RETRACTED".
Evaluation of Surface Energy Balance System (SEBS) Model for Estimation of Evapotranspiration in Eastern Ethiopia

Quantification of evapotranspiration (ET) is needed for a wide array of applications especially for water resources management. ET estimation by using either ground based direct measurement or modeling by using in-situ based meteorological variables is found cost inefficient or for some geographic areas it might be impractical. This issue is specially challenging in data scarce regions. This study evaluates remote sensing based surface energy balance system (SEBS) in arid and semi arid eastern Ethiopia. After undertaking a series of pre-processing and processing phases, surface parameters has been generated from MODIS level 1B products for dry season and dekadal composites from spot vegetation, down welling surface short web flux from LSA SAF and near surface meteorological variables from GLDAS has been utilized. By ingesting these parameters at prepackaged SEBS model, ET has been estimated. For comparative analysis, MSG ET with FAO-PM has been utilized. Our findings have shown that estimated ET ranges from 0 to 10 mm day -1 with large spatial variability. In areas that are well vegetated, SEBS provides larger values both at dry and wet seasons but at arid and semi-arid vast expanses of the study site there is found very lower ET value at dry season and increases with vegetation regeneration in the summer season. It was observed that at both dry and wet seasons SEBS ET values were over estimated than MSG ET product and underestimated than FAO-PM values. These under and over estimations were very large at arid and semi-arid areas which is attested from point based analysis undertaken using meteorological stations located at different climatic characteristics. Our study confirmed that, though SEBS model provides reasonable results it is sensitive for vegetation cover of a site. Taking these into consideration there should be comparative analysis of the model with direct field measurements for more certainty. Keywords : Evapotranspiration, Eastern Ethiopia, SEBS, Remote sensing
Erratum: Diluted mean-field spin-glass models at criticality

We present a method derived by cavity arguments to compute the spin-glass and higher order susceptibilities in diluted mean-field spin-glass models. The divergence of the spin-glass susceptibility is associated with the existence of a non-zero solution of a homogeneous linear integral equation. Higher order susceptibilities, relevant for critical dynamics through the parameter exponent λ, can be expressed at criticality as integrals involving the critical eigenvector. The numerical evaluation of the corresponding analytic expressions is discussed. The method is illustrated in the context of the de Almeida–Thouless line for a spin glass on a Bethe lattice but can be generalized straightforwardly to more complex situations.
Penalaran Matematis dan Kerja Keras Siswa Pembelajaran Matematika Berorientasi Teori APOS Berbantuan Permainan Monopoli

Berdasarkan pengalaman mengajar, ditemukan fakta bahwa proses belajar mengajar masih kurang dalam bagian penalaran. Siswa masih mengacu pada hafalan rumus dalam menyelesaikan masalah matematika, dan kurang memiliki karakter kerja keras ketika menemui permasalahan dengan variasi yang berbeda. Selain itu siswa cenderung banyak bermain dibandingkan belajar baik di rumah maupun di sekolah. Tuntutan pembelajaran yang menyenangkan bagi siswa akan dapat memacu guru untuk berinovasi dan berkreasi dengan menerapkan permainan dalam pembelajaran. Salah satu teori pembelajaran yang dapat mengajak siswa untuk beraktivitas dalam bernalar dan peningkatan karakter kerja keras adalah teori APOS. Berdasarkan uraian tersebut, maka tujuan dalam penulisan makalah ini adalah untuk mengetahui langkah/strategi serta metode apa yang bagus dan cocok untuk meningkatkan penalaran matematis siswa dan karakter kerja keras. Hasil dan pembahasan menyimpulkan bahwa pembelajaran matematika berorientasi teori APOS berbantuan permainan dapat meningkatkan penalaran matematis siswa dan karakter kerja keras.
Structural credit risk using time-changed Brownian motions : a tale of two models

We consider a structural credit risk framework introduced in [5] where the logleverage ratio of the firm is a Lévy process in the form of a time-changed Brownian motion (TCBM) where the time-change process has identically distributed independent increments. In models of this type, “vanilla” credit derivative pricing formulas are in closed form in terms of an explicit one-dimensional Fourier transform. Our primary aim is to investigate whether two very simple specifications of the time change process, namely the variance gamma (VG) model and the exponential jump model (EXP), can lead to good fits to CDS data for a representative firm with an interesting credit history, Ford Motor Co. Statistical inference in this class of intrinsically non-Gaussian hidden state models presents some new challenges which are a second main focus of the paper. We consider several variations of nonlinear filtering and statistical inference for TCBM models applied to a 4.5 year time series of credit default swap (CDS) prices on Ford, with the goal of finding a fast, accurate, robust scheme. The main conclusion is that the two TCBM models significantly outperform the classic Black-Cox model. Secondly, we show that a new inference method called the “linearized measurement scheme” is much faster than a standard numerical integration scheme (up to 100 times faster), and yields equivalent performance. The statistical methodology proposed in this paper can be effectively implemented for many other variations of TCBMs and applied to a wide range of firms, and opens the door to far-ranging explorations of a new class of structural credit risk models.
Beyond Fine Tuning: Adding capacity to leverage few labels

In this paper we present a technique to train neural network models on small amounts of data. Current methods for training neural networks on small amounts of rich data typically rely on strategies such as fine-tuning a pre-trained neural network or the use of domain-specific hand-engineered features. Here we take the approach of treating network layers, or entire networks, as modules and combine pre-trained modules with untrained modules, to learn the shift in distributions between data sets. The central impact of using a modular approach comes from adding new representations to a network, as opposed to replacing representations via fine-tuning. Using this technique, we are able surpass results using standard fine-tuning transfer learning approaches, and we are also able to significantly increase performance over such approaches when using smaller amounts of data.
Upwelling intensity and wave exposure determine recruitment of intertidal mussels and barnacles in the southern Benguela upwelling region

Marine larval dispersal and recruitment dynamics are fundamentally linked with nearshore circulation. In coastal upwelling systems, shoreline topography induces predictable circu- lation patterns, spanning a range of spatial and temporal scales. Based on a 5 yr time series of monthly recruitment of intertidal mussels and barnacles at 8 sites along 400 km of the southern Benguela upwelling region, which extends around the Cape of Good Hope, South Africa, we addressed the hypothesis that recruitment will exhibit spatial and temporal patterns reflecting the influence of topography and season on upwelling. Both taxa showed strongly seasonal recruitment peaks: mussels during the summer upwelling season and barnacles during spring. Spatially, mussels and barnacles differed in their regional-scale recruitment trends: recruitment of mussels increased northwards while that of barnacles peaked in the south. However, their mesoscale recruitment pat- terns were alike, with lower recruitment rates at headland upwelling centers than in adjacent bays. On a smaller scale of hundreds of meters, wave exposure had a positive effect on the recruitment of mussels and (to a lesser extent) barnacles. Spatial patterns were remarkably persistent over time and, for barnacles, strongly negatively correlated with upwelling, as quantified by a site-specific coastal upwelling index. The effect of temporal upwelling dynamics on recruitment was site dependent: mussel recruitment was strongly and positively correlated with upwelling at all sites, while barnacle recruitment showed a weak and spatially inconsistent link to upwelling fluctuations. The persistence of the spatial structure of recruitment and its coherence between unrelated taxa emphasizes the role of shoreline topography, thereby increasing our capacity to include regional-scale processes in the management and conservation of coastal ecosystems.