Miracle-dz/UniFAR-FTUs huggingface dataset:
MR Imaging of Gastric Carcinoma

Magnetic Resonance (MR) imaging has not become popular for staging of gastric carcinoma because of a number of limitations, including motion artifacts, lack of a stable contrast medium, and the high cost. However, continuous technical improvements have been made in MR imaging of the abdomen, thereby reducing motion artifacts and improving image quality. These improvements include breath-hold fast imaging techniques, placement of abdominal binders, administration of antiperistaltic agents, and the use of phased array coils. In vitro studies using 1 4.7T MR systems have shown that MRI allows the depiction of gastric wall layers and therefore, technically permits the evaluation of the local tumor stage of gastric carcinomas. However, MR study in gastric carcinoma is challenging and it has much possibility. Usually, the preoperative staging workup of gastric carcinoma is performed mainly with computed tomography (CT). CT has been a favored method for preoperative evaluation and staging in patients with gastric carcinoma (Goldberg & Thoeni. 1989; Werthmuller & Margulis. 1991; Halvorsen & Thompson. 1991). Parallel advances in CT equipment and scanning techniques have reduced scanning time and decreased motion artifacts. Simultaneously, rapid IV contrast administration with an automatic power injector has improved contrast enhancement of the gastric wall and gastric carcinoma. Helical CT has advantages over conventional CT, including faster scanning time and fewer respiratory misregistration artifacts in a single breath-hold (Hahn, et al., as cited in Stark & Bradley. 1992). However, CT is limited, particularly in the diagnosis of lymph node metastasis, peritoneal metastasis, and small hematogenous metastasis. Endoscopic sonography has been reported to be the most accurate technique for the T staging of gastric carcinoma because it can define five layers of the gastric wall (Botet, et al. 1991). But this technique cannot evaluate other factors such as liver metastasis and peritoneal seeding. In addition, endoscopic sonography is an invasive technique dependent on the operator.
Phase structure of radar stratigraphic horizons within Antarctic firn

Abstract We have recorded reflection profiles of firn through large areas of West Antarctica and part of the East Antarctic plateau using 400MHz short-pulse radar. The locations show accumulation rates that vary from well above to well below the vertical radar resolution. Most reflection horizons have extensive lateral continuity, and are composed of distinctive wavelets with a consistent phase polarity sequence within their successive half-cycles. We modeled these waveforms, and conclude that they arise from thin, double layers of ice over hoar, which is consistent with the standard model of firn stratification. In addition, we conclude that ice/hoar layers are extensive throughout West Antarctica and also present (although more sparsely) beneath the Antarctic Plateau.
Trust Metric based Soft Security in Mobile Pervasive Environment

In the decentralized and highly dynamic environment like Mobile Pervasive Environments (MPE) trust and security measurement are two major challenging issues for community researchers. So far primarily many of architectural frameworks and models developed and being used. In the vision of pervasive computing where mobile applications are growing immensely with the potential of low cost, high performance, and user centric solutions. This paradigm is highly dynamic and heterogeneous and brings along trust and security challenges regarding vulnerabilities and threats due to inherent open connectivity. Despite advances in the technology, there is still a lack of methods to measure the security and level of trust and framework for the assessment and calculation of the degree of the trustworthiness. In this paper, we explore security and trust metrics concerns requirement and challenges to decide the trust computations metric parameters for a self-adaptive self-monitoring trust based security assurance in mobile pervasive environment. The objective is to identify the trust parameters while routing and determine the node behavior for soft security trust metric. In winding up, we put our efforts to set up security assurance model to deal with attacks and vulnerabilities requirements of system under exploration. Index Terms—Metrics, Mobile Pervasive Environment (MPE), Security Assurance, Trust Metrics.
Young Travelers Different Perspective on a Muslim Destination Image and Travel Constraints

Different ethnic and/or racial groups vary in their leisure preferences and behaviors due to different constraints and affordances, as well as the destination image. However, there is few studies discussed the relationship and differences between destination image and travel constraints among people from different nations representing different cultures, not mention to understand potential culture influence on destination images and travel constraints. The youth tourism market was shown its significance from economic, social as well as cultural benefits to the destinations and the tourists. Studies showed that the young tourists usually traveled longer and more frequently than other segments of markets. This study was conducted to identify the young international travelers’ perception of a Muslim destination and the perceived travel constraints from cross-cultural perspective via Taiwan and America. There are three purposes of this study is threefold. First, this study is conducted to identify the perceptions of the youth market resulting from a Muslim destination image and associated travel constraints. Second, this study intends to depict the relationship between destination image and travel constraints as perceived by the young travelers cross cultural comparativeness. Third, to observe the Muslim cultures influence on the destination image and culture constraint for young international travelers.
Design of adaptive system of detection of cyber-attacks, based on the model of logical procedures and the coverage matrices of features

The results of the research aimed at the further development of detection models of cyber threats, as well as of common classes of anomalies and cyber-attacks in mission critical computer systems (MCCS) are presented. It is shown that one of the promising directions of synthesis of adaptive systems of detection and prevention of cyber-attacks is the application of models of logical procedures of detection, based on the coverage matrices of features of anomalies, threats and cyber-attacks within the known and new classes of the MCCS intrusions. The model of detection of cyber-attacks, anomalies and threats to MCCS was designed, which is based on the application of learning samples in the form of matrices of features and elementary classifiers for each of the modeled classes. The studies on minimization of the number of training samples, represented in a binary form of discerning features were carried out. The program "Threat Analyzer” was developed which allows automatic generation of dimensions of training matrix of features of anomalies, cyber threats, or cyber-attacks, without requiring the participation of experts. It is shown that for the object detection within known classes of cyber threats, attacks, anomalies, the usage in the training matrices of representative sets of 3-4 features long allows maximizing the effectiveness of the algorithm, reaching up to 98 %.
Extraventricular neurocytoma of the sellar region : report of two cases and literature review

Extraventricular neurocytoma (EVN) of the sellar region is a rare occurrence. To date, merely two reports concerning this tumor have been reported. In this report, we present two cases of EVN that occurred in the sellar region, and reviewed the pathological characteristics and treatment strategies for this disease. Two patients were admitted to our hospital for impaired vision. MRI scans indicated an enhanced invasive mass in the sellar region. One patient was treated via the subfrontal approach, and partial removal was achieved. The other patient was treated via the transsphenoidal approach by microscopy, and subtotal removal was achieved. Histologically, the tumor demonstrated typical features of neurocytoma, which presented nests, islands and strands of neuropil background. Immunohistochemistry (IHC) revealed diffuse Synaptophysin, MAP-2 and neurofilament positivity. Patients were diagnosed with EVN (WHO grade II) and adjuvant radiotherapy was given. In the present report, no loss of 1p/19q or atypical pathological feature was found. Furthermore, some of the molecular pathological characteristics of EVN were explored by literature review. Through these two cases, we confirm that EVN of the sellar region shares similar clinical pathological features with EVN of the other regions. Immunohistochemical examination is an effective method for the diagnosis of EVN. The preferred treatment for EVN of the sellar region is total removal by surgical approaches. Postoperative radiotherapy should be performed for tumors with atypical pathological features or when complete removal is not achieved.
Somatic embryogenesis and polyamines in woody plants

The formation of whole plants from cultured cells is interesting not only because of its applications for mass propagation but also as a prime example of the process of controlled development and differentiation in plants. Cultures capable of producing somatic embryos with high frequency provide ideal experimental systems to study and understand the biochemical basis of hormonal regulation of the developmental process. This knowledge should lead to the planning of media and various treatments that allow us to obtain whole plants from single cells in recalcitrant plant species.
Square Pulse Thermography (SPT) and Digital Speckle Photography (DSP): Non-Destructive Testing (NDT) Techniques Applied to the Defects Detection in Aerospace Materials

The use of composite materials is rapidly increasing in the production of aerospace structures. To match these advanced structures, a modern approach to their inspection and integrity monitoring is required. Composites are by nature inhomogeneous and anisotropic, establishing a good bond before the component enters service is paramount if the structure is to behave as expected by the designer. Constant strength throughout the structures life span requires periodic inspections, so that defects can be detected and eventually repaired at the lowest possible cost. Appropriate testing is needed to verify that the component is effectively bonded and has the required strength without damaging the part in any way. The principal defects that damage these materials are: delaminations, disbonds/unbonds, porosity, and cracks. In our paper, we have focused our attention on a glass fiber composite specimen with fabricated defects typically used for the lining of Agusta 109 LUH and Mc Donnel Douglass helicopters. The damage assessment methodology proposed is an integrated approach between two non-destructive techniques: square heating (SH) thermography and digital speckle photography (DSP). A comparative experimental investigation is discussed herein to evaluate the performance of SH and DSP for the non-destructive testing on this specimen.
Smart Network Field Theory: The Technophysics of Blockchain and Deep Learning

The aim of this paper is to propose a theoretical construct, smart network field theory, for the characterization, monitoring, and control of smart network systems. Smart network systems are intelligent autonomously-operating networks, a new form of global computational infrastructure that includes blockchains, deep learning, and autonomous-strike UAVs. These kinds of large-scale networks are a contemporary reality with thousands, millions, and billions of constituent elements, and entail a foundational and theoretically-robust model for their design and operation. Hence this work proposes smart network field theory, drawing from statistical physics, effective field theories, and model systems, for criticality detection and fleet-many item orchestration in smart network systems. Smart network field theory falls within the broader concern of technophysics (the application of physics to the study of technology), in which a key objective is deriving standardized methods for assessing system criticality and phase transition, and defining interim system structure between the levels of microscopic noise and macroscopic labels. The farther implications of this work include the possibility of recasting the P/NP computational complexity schema as one no longer based on traditional time (concurrency) and space constraints, due to the availability of smart network computational resources.
Classification dense d'images de profondeur entraînée sans données réelles

– Nous etudions le probleme de la segmentation semantique d'images de profondeur pour clusteriser les pixels d'une image qui appar-tiennent a une meme classe d'objet afin d'etendre les approches de localisation et cartographie (SLAM) a des cartes labellisees. Nous nous focaliserons sur les approches denses et directes qui exploitent l'ensemble des donnees fournies par un capteur, tel qu'une camera RGB-D grand-public. L'origina-lite de l'approche proposee reside dans l'apprentissage d'un reseau de neurones profond sans une masse de donnees reelles labellisees. Nous proposons une modelisation du capteur plus complete que les approches existantes pour generer des echantillons d'apprentissage a partir d'un modele virtuel. Les resultats demontrent que la modelisation du bruit du capteur permet d'obtenir une precision globale de 68.9% pour la classification semantique eparse d'images de profondeur encodees par representation HHA. Abstract – This paper studies the problem of semantic segmentation of depth maps clusterizing pixels of an image together which belong to the same objet class in order to extend SLAM technics with a labelled mapping. We focus on dense and direct approaches that harness whole data generated by a sensor, i.e. consumer RGB-D camera. What is original about this work is the training of a deep neural networks without a mass of real labelled data. A sensor model more complete than existing approachs generates training samples from a virtual model. Results show modeling sensor noise achieve a global precision of 68.9% in the case of sparse semantic segmentation of depth maps encoded with HHA representation.
Extraction of Novel Galactoarabinan-Rich Pectin with Gelling Capacity from Soursop Pomace

The effect of the strength of nitric acid-extractant (pH 1.2, 1.6, and 2.0) on the yield, sugar composition and molecular weight, and gelling ability of pectin from soursop (Annona muricata) was investigated to find out the optimum conditions for producing marketable pectin. The results showed that the yield (3.5-12.9%) of pectin (AMP) extracted from Annona muricata pomace was pH-dependent. Likewise, its galacturonic acid content (GalA: 41.3-72.8%), total neutral sugar content (TNS: 11.4-24.3%), methylesterification degree (DM: 64-82), viscosity-average-molecular weight (Mv: 62-105), and gelling capacity (GC: 98-163) were significantly influenced by the extraction pH (p 60%) with rather good yield (8.0%) and gelling power (>150).
The production of pronouns in Dutch children with developmental language disorders: A comparison between children with SLI, hearing impairment, and Down's syndrome

The production of pronouns in spontaneous language was investigated in three groups of children with Developmental Language Disorders (DLD): children with Specific Language Impairment (SLI), children with hearing impairment (HI), and children with Down's syndrome (DS). The results were compared to the production of pronouns in typically developing children, matched on MLUm. The number of pronouns produced did not differ significantly between the groups. In the order of production of pronouns, more commonalities than differences were found between the three DLD groups and compared to typically developing children. The number of errors in all groups appeared to be very low and all groups showed a significant correlation between the increase in MLU and the production of pronouns. The results are presented in relation to the discussion of whether children with DLD with different aetiologies show a difference in language behaviour.
Contrasts in sea ice deformation and production in the Arctic seasonal and perennial ice zones

[1] Four years (1997–2000) of RADARSAT Geophysical Processor System (RGPS) data are used to contrast the sea ice deformation and production regionally, and in the seasonal (SIZ) and perennial (PIZ) ice zones. Ice production is of seasonal ice in openings during the winter. Three-day estimates of these quantities are provided within Lagrangian elements initially 10 km on a side. A distinct seasonal cycle is seen in both zones with these estimates highest in the late fall and with seasonal minimums in the midwinter. Regional divergence over the winter could be up to 30%. Spatially, the highest deformation is seen in the SIZ north of coastal Alaska. Both ice deformation and production are higher in the SIZ: deformation-related ice production in the SIZ (∼0.5 m) is 1.5–2.3 times that of the PIZ (∼0.3 m): this is connected to ice strength and thickness. Atmospheric forcing and boundary layer structure contribute to only the seasonal and interannual variability. Seasonal ice growth in ice fractures accounts for ∼25–40% of the total ice production of the Arctic Ocean. Uncertainties in these estimates are discussed. By itself, this deformation-ice production relationship could be considered a negative feedback when thickness is perturbed. However, the overall effect on ice production in the face of increasing seasonal and thinner/weaker ice coverage could be modified by local destabilization of the water column promoting overturning of warmer water due to increased brine rejection; and the upwelling of the pynocline associated with increased occurrence of large shear motion in sea ice. Divergence is shown to be negligibly correlated to cyclonic motion in summer and winter in both ice zones.
How Important is Oil in Nigeria’s Economic Growth?

This study assesses the importance of oil in the development of the Nigerian economy in a multivariate VAR model over the period 1960-2009. Empirical evidence shows that the five subsectors are cointegrated and that the oil can cause other non oil sectors to grow. However, oil had adverse effect on the manufacturing sector. Granger causality test finds bidirectional causality between oil and manufacturing, oil and building & construction, manufacturing and building & construction, manufacturing and trade & services, and agriculture and building & construction. It also confirms unidirectional causality from manufacturing to agriculture and trade & services to oil. No causality was found between agriculture and oil, likewise between trade & services and building & construction. The paper recommends appropriate regulatory and pricing reforms in the oil sector to integrate it into the economy and reverse the negative impact of oil on the manufacturing sub sector.
Effect of Fish Protein Replacement in Diets for Juvenile Turbot Scophthalmus maximus

A dietary study was conducted to investigate the effect of partly substituted levels of fish meal in feed for juvenile (140500 g) turbot (Scophthalmus maximus Rafinesque) on growth performance. The experimental diets were formulated to contain 53, 73 and 93 % fish meal protein and different levels of plant protein substitutes (wheat meal, corn gluten meal, soybean meal and canola meal) with three replicates for each diet. Fish fed 53% fish meal diets had lower final mean weights compared to fish fed the 93% fish meal diet, whereas the 73% fish meal group displayed intermediate values. However, only minor differences were found in specific growth rate, feed conversion ratio, daily feed intake and total feed consumption between dietary treatment groups. Overall the findings demonstrate that substitution of fish meal by plant protein raw materials down to 53 % fish meal protein (44% replacement) does not affect overall specific growth rate, feed conversion ratio or feed intake in juvenile turbot (<500 g).
A Recursive Coalescing Method for Bisecting Graphs

We present an extension to a hybrid graph-bisection algorithm developed by Bui et al. that uses vertex coalescing and the Kernighan-Lin variabledepth algorithm to minimize the size of the cut set. In the original heuristic technique, one iteration of vertex coalescing is used to improve the performance of the original Kernighan-Lin algorithm. We show that by performing vertex coalescing recursively, substantially greater improvements can be achieved for standard random graphs of average degree in the range [2:0; 5:0]. Subject classi cations: networks/graphs, heuristics: algorithms for graph bisection. Additional keywords: combinatorial optimization, design of algorithms, empirical analysis of algorithms, heuristic search. This paper is available from the Center for Research in Computing Technology, Division of Applied Sciences, Harvard University as Technical Report TR-19-94.
Survey on Itemset Mining from Transactional Database

: Itemset mining is an important task in data mining. Discovering useful patterns hidden in a database plays an essential role in several data mining tasks, such as frequent itemset mining, weighted frequent itemset mining and high utility itemset mining. Frequent itemset mining extracts items without consideration of user’s interest. Weighted itemset mining considers weights of an item to get most useful itemsets. Utility mining is an emerging area in itemset mining. It considers both quantity and profit an item to extract high utility items. Lot of research work done in itemset mining. Now a day, more focus is on utility itemset mining. This paper surveys approaches of frequent itemset mining, weighted frequent itemset mining and utility itemset mining.
Factors affecting wild rabbit production in extensive breeding enclosures: how can we optimise efforts?

The decline in the rabbit population in the Iberian Peninsula has led hunters and authorities to rear rabbits in captivity systems for the purpose of their subsequent release. An alternative method to intensive rabbitry systems is extensive breeding enclosures, since they produce animals of a greater quality for hunting and conservation purposes. However, some of the factors that affect rabbit production in breeding enclosures are still unknown. We have therefore used partial least squares regression (PLSR) to analyse the effect of plot size, scrub cover, slope, initial rabbit abundance, the resources needed to dig warrens, predation and proximity to others enclosures. The results of our study show that the number of other fenced plots within a radius of 3 km, the scrub cover and the optimal resources needed to dig warrens affect rabbit abundance. According to our results, in order to maximize rabbit production in the enclosures it would be advisable to concentrate the restocking effort by ensuring that the restocking plots are close to each other, thus avoiding isolated enclosures. Furthermore, the selection of plots with an appropriate protection similar to that of natural warren construction, such as large stones or tall shrubs, may optimize results.