Miracle-dz/UniFAR-FTUs huggingface dataset:
Forensics of Features in the Spectra of Biological Signals

Semantics of spectroscopy of biological signals and criteria of semantic stability are the initial issues in this article. Motivated with some semantic confusion related to our cooperation and elsewhere, we are investigating the circumstances in which spectroscopic features have direct meaning and when that is questioned. Two problems arise immediately: what are additional ways in signal analysis through spectroscopy and generalizations and how can we learn more on the processes investigated. Our aim is to enrich the available methods and tools providing researchers with additional ways in detailed analysis of biological signal spectra and help to overcome some of difficulties. We show some of our work in signal spectroscopy, aiming to signal forensics and to uncover more details in the investigated signals, discuss invariants of involved operators, addressing the WYSIWYG “what you see is what you get” method property. Ziggurat like structures of spectral features, parallel multiple resolution spectroscopy, application of image processing tools on spectral features and second order spectroscopy take place in the investigation of fine spectrogram feature details. Automatized feature detection and comparisons techniques, are used. These set of procedures represent our improvements and contribution to this important method for analysis of biological signals, illustrated on the examples from our practice, processed with our implementations.
Determining optimum rate of boron application for higher yield of wheat in Old Brahmaputra Floodplain soil

The effect of different rates of boron application on wheat cv. Bijoy was studied through a field experiment at Bangladesh Agricultural University (BAU) farm, Mymensingh during 2009-10 rabi season. The BAU farm belongs to Old Brahmaputra Floodplain agroecological zone (AEZ 9). Texturally the soil was silt loam, with 7.2 pH, 0.81% organic matter and 0.15 mg kg-1 available boron content. The experiment was laid out in a randomized complete block design with five boron rates and four replications. Boron rates were 0, 0.75, 1.5, 2.25 and 3.0 kg ha-1, with boric acid as a source. Every plot received blanket doses of 115 kg N, 25 kg P, 75 kg K and 15 kg S ha-1 from urea, TSP, MoP and gypsum, respectively. Treatment receiving B @ 2.25 kg ha-1 produced the highest grain yield (4.22 t ha-1) which was statistically identical with that obtained with 1.75 kg B ha-1. However, the crop response curve showed 1.90 kg ha-1 to be the optimum boron rate for the maximization of wheat yield. The lowest grain yield (2.84 t/ha) was recorded with control treatment. There was a positive relationship between grain yield and number of grains spike-1. Boron had significant influence on N, P, K, S and B uptake by the crop which, in deed, was more influenced by crop yield and less by nutrient concentration, except N and B uptake where concentration had more influence than yield.
Isolation of Arcobacter spp from the milk of dairy cows in Brazil

Bacteriologic examinations were performed on 188 milk samples collected from cows from 11 farms for diagnosis of mastitis in three cities of Rio Grande do Sul, Brazil. Among the common causes of mastitis, the most frequent isolates were Staphylococcus aureus, followed by Corynebacterium sp, Streptococcus uberis, Streptococcus dysgalactiae and Streptococcus agalactiae. Bacteriologic examination of 32 milk samples from one farm didn't show bacteria known as common etiologic agent of mastitis. Six samples of Arcobacter spp typed by genotypic tests as Arcobacter cryaerophilus (five strains) and Arcobacter butzleri (one strain) were isolated from cows' milk of that farm. It is reported the isolation of Arcobacter species from the milk of cows in absence of clinical signs of mastitis. This is the first report of the detection of the microorganisms in the milk of dairy cows in Brazil. No previous reports are known from other countries.
KCNN: Extremely-Efficient Hardware Keypoint Detection with a Compact Convolutional Neural Network

Keypoint detection algorithms are typically based on handcrafted combinations of derivative operations implemented with standard image filtering approaches. The early layers of Convolutional Neural Networks (CNNs) for image classification, whose implementation is nowadays often available within optimized hardware units, are characterized by a similar architecture. Therefore, the exploration of CNNs for keypoint detection is a promising avenue to obtain a low-latency implementation, also enabling to effectively move the computational cost of the detection to dedicated Neural Network processing units. This paper proposes a methodology for effective keypoint detection by means of an efficient CNN characterized by a compact three-layer architecture. A novel training procedure is proposed for learning values of the network parameters which allow for an approximation of the response of handcrafted detectors, showing that the proposed architecture is able to obtain results comparable with the state of the art. The capability of emulating different detectors allows to deploy a variety of algorithms to dedicated hardware by simply retraining the network. A sensor-based FPGA implementation of the introduced CNN architecture is presented, allowing latency smaller than 1 [ms].
Distribution of Pelagic Elasmobranchs Caught by Salmon Research Gillnets in the North Pacific

The distribution of pelagic elasmobranchs was analyzed using bycatch data from the high seas salmon surveys by research gillnets from 1981 to 1991 in the North Pacific Ocean and the Bering Sea. Five species of sharks and one stingray were reported. Blue and salmon sharks and spiny dogfish were dominant and constituted 98% of the total shark catch. It is considered that the research area includes the southern part of the distribution for spiny dogfish and salmon sharks and the northern part of that for blue, shortfin mako, cookiecutter sharks and pelagic stingrays. These elasmobranchs showed spa tial segregation by species in distribution according to oceanographic conditions. Intraspecific sexual and growth dependent segregations were also confirmed. Length frequency distributions of blue and salmon sharks suggest that their nursery grounds exist around the transitional domain of the subarctic boundary. The Japanese high-seas salmon fishery ceased in 1992 af ter some 40 years of industrial fishing from 1952 because of international concern about the impact of this fishery upon the oceanic ecosystem. The Fisheries Agency of Japan has conducted salmon research for the rational use of salmon stocks for a long time. It also started bycatch research in the 1970 s using several research vessels. Bycatch research data collected by the research vessels of Hokkaido University and chartered vessels for scientific research from 1981 to 1991 were used for the present analy sis. The research area is widely distributed from 35? N 63°N from the northern coast of Japan to the Gulf of Alaska and the Bering Sea. The spatial distribution and migration of pelagic elas mobranchs are still poorly known, although several sur veys were conducted in the North Pacific Ocean.1-6) Many of those studies partly described their distributions and migrations due to the limitation of research area, season and gear selectivity. Therefore, more detailed biological and ecological information is necessary for the conserva tion and stock management of pelagic elasmobranchs. This paper describes the distribution of pelagic sharks and rays in the North Pacific, north of the subarctic boundary.
Details-First, Show Context, Overview Last: Supporting Exploration of Viscous Fingers in Large-Scale Ensemble Simulations

Visualization research often seeks designs that first establish an overview of the data, in accordance to the information seeking mantra: “Overview first, zoom and filter, then details on demand”. However, in computational fluid dynamics (CFD), as well as in other domains, there are many situations where such a spatial overview is not relevant or practical for users, for example when the experts already have a good mental overview of the data, or when an analysis of a large overall structure may not be related to the specific, information-driven tasks of users. Using scientific workflow theory and, as a vehicle, the problem of viscous finger evolution, we advocate an alternative model that allows domain experts to explore features of interest first, then explore the context around those features, and finally move to a potentially unfamiliar summarization overview. In a model instantiation, we show how a computational back-end can identify and track over time low-level, small features, then be used to filter the context of those features while controlling the complexity of the visualization, and finally to summarize and compare simulations. We demonstrate the effectiveness of this approach with an online web-based exploration of a total volume of data approaching half a billion seven-dimensional data points, and report supportive feedback provided by domain experts with respect to both the instantiation and the theoretical model.
The pathway of uptake of SV 40 pseudovirions packaged in vitro : from MHC class I receptors to the nucleus Research Article

Chava Kimchi-Sarfaty, Susan Garfield, Nathan S. Alexander, Saadia Ali, Carlos Cruz, Dhanalakshmi Chinnasamy, and Michael M. Gottesman* Laboratory of Cell Biology, Laboratory of Experimental Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA Vince Lombardi Gene Therapy Laboratory, Immunotherapy Program, St. Luke’s Medical Center, Milwaukee, WI 53215, USA
An approximation algorithm for the Steiner connectivity problem

This article presents an approximation algorithm for the Steiner connectivity problem, which is a generalization of the Steiner tree problem that involves paths instead of edges. The problem can also be seen as hypergraph‐version of the Steiner tree problem; it arises in line planning in public transport. We prove a k+1 approximation guarantee, where k is the minimum of the maximum number of nodes in a path minus 1 and the maximum number of terminal nodes in a path. The result is based on a structural degree property for terminal nodes.
Supporting Redesign of C2C Services Through Customer Journey Mapping

It is challenging for service companies to obtain a detailed overview of their customers' endto-end service delivery processes. This paper extends previous work on a structured approach for modelling customer journeys to encompass complex, technology-driven service systems. We report on how the approach can support documentation and analysis of service delivery from a customer perspective, and present a case study of a consumer-to-consumer (C2C) service in an eMarket company. The case study involved mapping of the service process as intended by the service provider (planned journey), as well as customer journeys as experienced by users (actual journey). Our results reveal that the approach supported the eMarket company in obtaining a detailed overview of the service process, and in understanding the customers' experiences. Deviations between planned and actual journeys uncovered user issues and gaps in the service delivery, pointing to parts of the journey that were prone for improvements and redesign.
Retrieval and analysis of stratospheric NO2 from the Global Ozone Monitoring Experiment

[1] We describe the retrieval of stratospheric NO2 vertical column densities from the Global Ozone Monitoring Experiment (GOME) aboard the ERS-2 satellite. Different differential optical absorption spectroscopy (DOAS) evaluations are compared in order to investigate uncertainties caused by the diffuser plate. An improved version of our algorithm to separate the tropospheric and stratospheric fraction of NO2 from GOME satellite data is described and is used to extract a long term data set of stratospheric NO2 (1996–2000). In addition, the average seasonal variation in the global distribution is determined, which allows us to monitor and investigate specific aspects of stratospheric chemistry, in particular the interhemispheric comparison of stratospheric NO2. In contrast to other satellite observations (e.g., SAGE II, OSIRIS), GOME observations of stratospheric NO2 include the lower stratosphere. In general, our observations are in agreement with previous measurements and confirm the current knowledge of stratospheric nitrogen chemistry.
PREPARATION AND EVALUATION OF SODIUM ALGINATE POROUS DOSAGE FORM AS CARRIERS FOR LOW DOSED ACTIVE PHARMACEUTICAL INGREDIENTS

The present investigation was undertaken to fabricate porous controlled release dosage form of metoprolol tartarate using sodium alginate (SA) as a matrix forming agent and ammonium carbonate (AC) as a pore forming agent. This study evaluated a novel approach and newer technique for development of low dosed tablets by direct compression technique. Tablets were evaluated for pharmacotechnical properties and results were found to be satisfactory. Influence of pore forming agent on properties of tablets were mainly investigated. FTIR, DSC were conducted in order to show drug, polymer excipient compatibility. SEM studies were conducted in order to show the porous surface of tablets. Ammonium carbonate as a pore forming agent proves to be promising and was successful in creating pores on surface of tablets through which drug was loaded in tablets. SEM had given a clear picture showing major and minor pore with different pore size. Response Surface Curves (RSC) had been plotted in order to see the effect of pore forming agent on properties of tablets (disintegration, hardness and drug release). It was found that an increase in pore forming agent leads to decrease in hardness and disintegration time of porous tablets. Drug release was found to be drastically affected by concentration of pore forming agent present in respective batches of tablets. In-vitro release data shows that tablets follow zero order release mechanism which was further confirmed by Korsmeyer-Peppas, indicating that more than one mechanism for the drug release are involved, that is diffusion and erosion.
Landslide Disaster Management and Planning A GIS based Approach

Landslide hazard zonation helps in identifying strategic points and geographically critical areas prone to landslides. In this study, a methodology has been developed to identify landslide prone areas using Photogrammetry with 3D GIS. A small area in the Kothagiri taluk of the Nilgiris district has been selected for this study. Orthophoto map was generated by ORTHOCOMP from aerial photograph on 1: 8,000 scale. The advantage of the high-resolution data helps in deriving 2 m contour, which is ideal to get the elevation and slope values of the terrain. The products derived from DEMs are contour maps (2 m interval), slope maps, aspect maps, shaded relief maps and perspective views. The orthophoto map, topographic map, land-use/ land-cover map, slope map, soil map, geology, transportation network, and relative relief map have been utilized to generate various thematic data layers in GIS environment. In order to get the landslide prone areas, the triggering criteria should be assigned to each map layer. Depending on the threat posed by each category the Landslide Susceptibility Index, i.e., weightages were assigned. The data layers have been integrated in GIS environment by overlay analysis. The zonation map divides the study area into four zones of landslide vulnerability viz., very high, high, moderate and low. Arc view  3D analyst was used especially for generating 3D view and getting slope and aspect information. Overview
Liquefaction Processes And Characterization Of Liquefied Products From Waste Woody Materials In Different Acidic Catalysts

The liquefaction process is one of the promising techniques for effective utilization of woody biomass, for the lignocelluloses can be converted to liquid reactive material, as eco-polymeric materials. Japanese cedar (Cryptomeria Japonica), as an abundant waste softwood material, was selected and used in our wood liquefaction experiment. In order to investigate the basic characteristics and potentially harmful metal contents, the composition and metal elements of waste woody samples had been determined, and based on the methods of Japanese Industrial Standard (JIS) and by an ICP-AES, separately. Then the waste woody samples were liquefied by a phenol wood liquefaction according to the orthogonal test L9 (3 4 ), in order to obtain relatively less residue by different reaction conditions. It is thought that sulfuric acid plays an important role in retarding the condensation reaction during the acid-catalyzed phenol liquefaction because of the dehydration, and it can be summarized that the most influential factors of the wood liquefaction conditions were obtained within the setting ranges on four factors and three levels by using the orthogonal tests. In the acidic catalyst comparison experiment, as a result, when using concentrated sulfuric acid as the strong acidic catalyst, the minimum of residual content had reached 9.71%. According to these experimental results, the new liquefied samples
Computer Simulation in Hospitality Teaching, Practice, and Research

Excerpt] This paper focuses on the use of computer simulation as a tool and how it can be applied in hospitality education, practice, and research. Simulation involves the modeling of an existing real system—for example, skiers' activities at a ski resort, diners' experiences in a full-service restaurant, and guests' transactions at a hotel's front desk. In this article we first discuss the main types of simulation—numerical simulation and discrete-event simulation. We then discuss the tools for building simulation models and offer a few words of caution regarding simulation. We close with our thoughts about the usefulness of computer-simulation modeling.
Heat source identification based on l1 constrained minimization

We consider the inverse problem of finding sparse initial data from the sparsely sampled solutions of the heat equation. The initial data are assumed to be a sum of an unknown but finite number of Dirac delta functions at unknown locations. Point-wise values of the heat solution at only a few locations are used in an $l_1$ constrained optimization to find the initial data. A concept of domain of effective sensing is introduced to speed up the already fast Bregman iterative algorithm for $l_1$ optimization. Furthermore, an algorithm which successively adds new measurements at specially chosen locations is introduced. By comparing the solutions of the inverse problem obtained from different number of measurements, the algorithm decides where to add new measurements in order to improve the reconstruction of the sparse initial data.
Kinematic Pose Rectification for Performance Analysis and Retrieval in Sports

The automated extraction of kinematic parameters from athletes in video footage allows for direct training feedback and continuous quantitative assessment of an athlete's performance. Recent developments in the field of deep learning enable the measurement of kinematic coefficients directly from human pose estimates. However, the detection quality decreases while errors and noise increase with the complexity of the scene. In aquatic training scenarios, for instance, continuous pose estimation suffers from several orthogonal errors like switched joint predictions between the left and right sides of the body. In this paper, we analyze different error modes and present a rectification pipeline for improving the pose predictions using merely joint coordinates. We show experimentally that joint rectification equally improves the detection of key-poses, which are essential for a continuous qualitative performance assessment and pose retrieval, as well as posture visualization for quantitative training feedback.
Using The Noise Density Down Projection To Expose Splicing In JPEG Images

In digital image forensics, the detection of exogenous elements in an image is a difficult open problem, and several ways to solve it have already been proposed. In this paper, we use differences in the intrinsic noise in digital images to highlight this type of forgery. Our method analyses an histogram based on the noise density function at the local level in order to reveal suspicious areas, by using a new tool exploiting the uniform property of the Gaussian noise contained in JPEG images. Although the use of noise discrepancies to detect splicing has already been done multiple times, most existing methods tend to perform poorly on the current generation of high quality images, with high resolution and low noise. The improvements of our method over other state of the art approaches is demonstrated on a large set of randomly spliced natural images.
Ecology of Argali in Ikh Nartiin Chuluu, Dornogobi Aymag.

Argali sheep (Ovis ammon) are listed as threatened in both Mongolia and internationally. Yet, little is known about the biology and ecology of this species. Available data suggests that Argali in Mongolia are declining due to direct poaching and competition with domestic livestock. We initiated several research projects to better understand and conserve the species. In this report we discuss Argali ecology using radio telemetry. We captured and radio-collared 36 Argali using drive-nets, lamb captures, and darting from 2000–2004. Fifteen collared animals have died: 2 due to capture techniques, 8 from predation, 1 from starvation and exposure, 1 from disease, 1 due to maternal neglect, and 2 of unknown causes. In addition, 1 collar ceased working and 4 others dropped off prematurely. We have collected more than 1,040 locations through mid-May 2004. The majority of the Argali were captured in the northern portion of Ikh Nart. Animals have primarily restricted their movements to that area and have not exhibited seasonal movement patterns. Mean home range size for 17 animals with sufficient data (45 days with locations) was 57 ±3.7km 2 (range= 30– 80km 2 ) using the 100% minimum convex polygon method, with areas of predicted occurrence of 76 ±5.3km 2 for 95% kernel, 32 ±3.7km 2 for 75% kernel, 11 ±1.6km 2 for 50% kernel, and 3.8 ±0.5km 2 for 25% home ranges. Predation was the main cause (72.7%) of mortality in the collared animals for which cause of death could be determined (non-study related).
Microscopic simulation of stress correlation evolution: implication for the critical point hypothesis for earthquakes.

It has been argued that power-law time-to-failure fits for cumulative Benioff strain and an evolution in size-frequency statistics in the lead-up to large earthquakes is evidence that the crust behaves as a Critical Point (CP) system. If so, intermediate–term earthquake prediction is possible. However, this hypothesis has not been proven. If the crust does behave as a CP system, stress correlation lengths should grow in the lead-up to large events and drop sharply once these occur. However, this evolution in stress correlation lengths cannot be observed directly. Here, we show using the lattice solid model to describe discontinuous elasto-dynamic systems subjected to shear and compression, that it is for possible correlation lengths to exhibit CP-type evolution. This provides the first direct evidence that systems with realistic elasto-dynamics may behave as CP systems, and hence supports the Critical Point hypothesis for earthquakes.