Miracle-dz/UniFAR-FTUs huggingface dataset:
Methodology of technological evolution for three-dimensional printing

Purpose – An increasing amount of attention is being paid to three-dimensional (3D) printing technology. The technology itself is based on diverse technologies such as laser beams and materials. Hence, 3D printing technology is a converging technology that produces 3D objects using a 3D printer. To become technologically competitive, many companies and nations are developing technologies for 3D printing. So to know its technological evolution is meaningful for developing 3D printing in the future. The paper aims to discuss these issues. Design/methodology/approach – To get technological competitiveness of 3D printing, the authors should know the most important and essential technology for 3D printing. An understanding of the technological evolution of 3D printing is needed to forecast its future technologies and build the R & D planning needed for 3D printing. In this paper, the authors propose a methodology to analyze the technological evolution of 3D printing. The authors analyze entire patent documents.
Fast and flexible string matching by combining bit-parallelism and suffix automata

The most important features of a string matching algorithm are its efficiency and its flexibility. Efficiency has traditionally received more attention, while flexibility in the search pattern is becoming a more and more important issue. Most classical string matching algorithms are aimed at quickly finding an exact pattern in a text, being Knuth-Morris-Pratt (KMP) and the Boyer-Moore (BM) family the most famous ones. A recent development uses deterministic "suffix automata" to design new optimal string matching algorithms, e.g. BDM and TurboBDM. Flexibility has been addressed quite separately by the use of "bit-parallelism", which simulates automata in their nondeterministic form by using bits and exploiting the intrinsic parallelism inside the computer word, e.g. the Shift-Or algorithm. Those algorithms are extended to handle classes of characters and errors in the pattern and/or in the text, their drawback being their inability to skip text characters. In this paper we merge bit-parallelism and suffix automata, so that a nondeterministic suffix automaton is simulated using bit-parallelism. The resulting algorithm, called BNDM, obtains the best from both worlds. It is much simpler to implement than BDM and nearly as simple as Shift-Or. It inherits from Shift-Or the ability to handle flexible patterns and from BDM the ability to skip characters. BNDM is 30%-40% faster than BDM and up to 7 times faster than Shift-Or. When compared to the fastest existing algorithms on exact patterns (which belong to the BM family), BNDM is from 20% slower to 3 times faster, depending on the alphabet size. With respect to flexible pattern searching, BNDM is by far the fastest technique to deal with classes of characters and is competitive to search allowing errors. In particular, BNDM seems very adequate for computational biology applications, since it is the fastest algorithm to search on DNA sequences and flexible searching is an important problem in that area. As a theoretical development related to flexible pattern matching, we introduce a new automaton to recognize suffixes of patterns with classes of characters. To the best of our knowledge, this automaton has not been studied before.
Alcohol Myopia Revisited

The alcohol myopia model (AMM; Steele & Josephs, 1990) is reviewed in light of its unique ability to account for a variety of alcohol and nonalcohol-related disinhibited behaviors, particularly aggression. The AMM posits that alcohol has a narrowing, or a “myopic,” effect on one’s ability to attend to competing instigatory and inhibitory cues. Disinhibited behavior is presumed to occur when attention is directed toward salient provocative or instigatory cues rather than inhibitory cues. AMM research is reviewed with regard to stress and anxiety, risky sexual behavior, drinking and driving, suicide, disinhibited eating, smoking, and alcohol-related aggression. The AMM is also expanded by proposing five key mechanisms (i.e., negative affect, angry affect, hostile cognitive rumination, self-awareness, and empathy) that are likely to explain how the model is specifically involved in the alcohol-aggression relation. Finally, a number of public health interventions, extrapolated from the AMM, are proposed to stimulate future research directed at reducing the prevalence of alcohol-related violence.
On optimal regularity of free boundary problems and a conjecture of De Giorgi

We present a general theory to study optimal regularity for a large class of nonlinear elliptic systems satisfying general boundary conditions and in the presence of a geometric transmission condition on the free boundary. As an application we give a full positive answer to a conjecture of De Giorgi on the analyticity of local minimizers of the Mumford‐Shah functional. © 2004 Wiley Periodicals, Inc.
Motion Blur Rendering: State of the Art

Motion blur is a fundamental cue in the perception of objects in motion. This phenomenon manifests as a visible trail along the trajectory of the object and is the result of the combination of relative motion and light integration taking place in film and electronic cameras. In this work, we analyse the mechanisms that produce motion blur in recording devices and the methods that can simulate it in computer generated images. Light integration over time is one of the most expensive processes to simulate in high‐quality renders, as such, we make an in‐depth review of the existing algorithms and we categorize them in the context of a formal model that highlights their differences, strengths and limitations. We finalize this report proposing a number of alternative classifications that will help the reader identify the best technique for a particular scenario.
Efficient mining of emerging patterns: discovering trends and differences

We introduce a new kind of patterns, called emerging patterns (EPs), for knowledge discovery from databases. EPs are defined as itemsets whose supports increase significantly from one dataset to another. EPs can capture emerging trends in timestamped databases, or useful contrasts between data classes. EPs have been proven useful: we have used them to build very powerful classifiers, which are more accurate than C4.5 and CBA, for many datasets. We believe that EPs with low to medium support, such as 1%-20%, can give useful new insights and guidance to experts, in even “well understood” applications. The efficient mining of EPs is a challenging problem, since (i) the Apriori property no longer holds for EPs, and (ii) there are usually too many candidates for high dimensional databases or for small support thresholds such as 0.5%. Naive algorithms are too costly. To solve this problem, (a) we promote the description of large collections of itemsets using their concise borders (the pair of sets of the minimal and of the maximal itemsets in the collections). (b) We design EP mining algorithms which manipulate only borders of collections (especially using our multiborder-differential algorithm), and which represent discovered EPs using borders. All EPs satisfying a constraint can be efficiently discovered by our border-based algorithms, which take the borders, derived by Max-Miner, of large itemsets as inputs. In our experiments on large and high dimensional datasets including the US census and Mushroom datasets, many EPs, including some with large cardinality, are found quickly. We also give other algorithms for discovering general or special types of EPs. Permission to make digital or hard copies of all or part ol‘this work Iht personal or classroom USC is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the lirst page. To copy otherwise, to republish, to post on servers or to redistribute to lists. requires prior specific permission and/or a fee. KDD-99 San Diego CA USA Copyright ACM 1999 l-58113-143-7/99/08. $5.00 Jinyan Li Department of CSSE The University of Melbourne jyli@cs.mu. oz.au
Dream to Predict? REM Dreaming as Prospective Coding

The dream as prediction seems inherently improbable. The bizarre occurrences in dreams never characterize everyday life. Dreams do not come true! But assuming that bizarreness negates expectations may rest on a misunderstanding of how the predictive brain works. In evolutionary terms, the ability to rapidly predict what sensory input implies—through expectations derived from discerning patterns in associated past experiences—would have enhanced fitness and survival. For example, food and water are essential for survival, associating past experiences (to identify location patterns) predicts where they can be found. Similarly, prediction may enable predator identification from what would have been only a fleeting and ambiguous stimulus—without prior expectations. To confront the many challenges associated with natural settings, visual perception is vital for humans (and most mammals) and often responses must be rapid. Predictive coding during wake may, therefore, be based on unconscious imagery so that visual perception is maintained and appropriate motor actions triggered quickly. Speed may also dictate the form of the imagery. Bizarreness, during REM dreaming, may result from a prospective code fusing phenomena with the same meaning—within a particular context. For example, if the context is possible predation, from the perspective of the prey two different predators can both mean the same (i.e., immediate danger) and require the same response (e.g., flight). Prospective coding may also prune redundancy from memories, to focus the image on the contextually-relevant elements only, thus, rendering the non-relevant phenomena indeterminate—another aspect of bizarreness. In sum, this paper offers an evolutionary take on REM dreaming as a form of prospective coding which identifies a probabilistic pattern in past events. This pattern is portrayed in an unconscious, associative, sensorimotor image which may support cognition in wake through being mobilized as a predictive code. A particular dream illustrates.
Clinical role of HER-2/neu expression in colorectal cancer.

PURPOSE To evaluate the HER-2/neu expression and its relationship with clinicopathological parameters and prognosis in colorectal cancer patients. METHODS A total of 51 colorectal cancer patients who underwent resection with curative intent from January 2005 to March 2006 were included in this study. Patients were regularly followed up and survival data were obtained as of as April 2011. HER-2/neu protein expression was evaluated from tissue samples from the primary tumor using a semiquantitative standardized immunohistochemical staining kit. Staining intensity was scored as faint (1+), weak to moderate (2+) and moderate to strong (3+). RESULTS Forty-nine (96.1%) patients showed 1+ staining, 2 (3.9%) 2+, while no case was strongly positive (3+) for HER-2/neu. No apparent association was noted between HER-2/neu expression and patients' age, gender, tumor location, tumor grade, stage and survival. CONCLUSION Moderate (2+) overexpression of HER-2/neu was detected in a small proportion of colorectal cancer patients. Considering the low rate of HER-2/neu overexpression in colorectal cancer, studies with larger sample sizes using standardized tests are essential to understanding the biologic role of HER-2/neu in this disease.
SIGNIFICANCE OF THE ULTRASOUND LOCATION OF PLACENTAL SITE IN EARLY PREGNANCY

The placenta was located by routine ultrasound scanning before 24 weeks gestation in 615 consecutive obstetric patients. A ‘low lying’ placenta was present in 175 (28 per cent) of the total group; the incidence decreasing from 32 per cent at 16 weeks gestation to 18 per cent at 24 weeks. Of 94 women with an initial ‘low lying’ placenta who were selected for rescanning, only five had a placenta praevia persisting beyond the 34th week. Patients with an early ‘low lying’ placenta had a significantly higher incidence of small‐for‐dates babies than those in whom the placenta remained clear of the internal cervical os on ultrasound scanning.
A Study of Online Portal Users’ Loyalty From Core Service, Additional Value-added Service and Switching Barriers Perspectives

This study proposes a research model elucidating the effects of core service satisfaction, additional value-added service satisfaction, and switching barriers as determinants of portal loyalty and tests the model using empirical data collected from game portal users. The results suggest that different service satisfaction and switching barriers are strong antecedents of p-loyalty; the moderating effect of switching barriers on the relationship between satisfactions and p-loyalty is contingent on the portal users’ usage patterns.
A new maximum power point tracking method for PV systems under partially shaded conditions

This paper proposes a new method which can track the maximum power under partially shaded conditions (PSC). Global maximum power (GPmax) searching method is used in this study, that is obtained by combining incremental conductance (IncCond) and scanning approach method which utilizes duty cycle sweep to track the global maximum when the PV array operates under PSC. This method is used in photovoltaic (PV) array simulation model that established in MATLAB/Simulink simulation platform. This study shows that the proposed method can track the real maximum power point accurately.
Revisiting the problem of audio-based hit song prediction using convolutional neural networks

Being able to predict whether a song can be a hit has important applications in the music industry. Although it is true that the popularity of a song can be greatly affected by external factors such as social and commercial influences, to which degree audio features computed from musical signals (whom we regard as internal factors) can predict song popularity is an interesting research question on its own. Motivated by the recent success of deep learning techniques, we attempt to extend previous work on hit song prediction by jointly learning the audio features and prediction models using deep learning. Specifically, we experiment with a convolutional neural network model that takes the primitive mel-spectrogram as the input for feature learning, a more advanced JYnet model that uses an external song dataset for supervised pre-training and auto-tagging, and the combination of these two models. We also consider the inception model to characterize audio information in different scales. Our experiments suggest that deep structures are indeed more accurate than shallow structures in predicting the popularity of either Chinese or Western Pop songs in Taiwan. We also use the tags predicted by JYnet to gain insights into the result of different models.
ROBAC: Scalable Role and Organization Based Access Control Models

In RBAC, roles are typically created based on job functions inside an organization. Traditional RBAC does not scale up well for modeling security policies spanning multiple organizations. To solve this problem, a family of extended RBAC models called role and organization based access control (ROBAC) models is proposed and formalized in this paper. Two examples are used to motivate and demonstrate the usefulness of ROBAC. Comparison between ROBAC and other related RBAC models is given. We show that ROBAC can significantly reduce administration complexity for Web and Internet-based applications involving a large number of organizations. Some administrative issues for ROBAC are identified and discussed. Although the theoretical-expressive power of ROBAC is the same as that of RBAC, it is more succinct and intuitive to use ROBAC than to use RBAC when applications involve many organizations
Soft X-Ray Scattering and Halos from Dust

Small-angle scatterings of X-rays by interstellar dust particles create halos around X-ray sources. The halo intensity and its projected radial distribution around a source can provide important information on the spatial distribution of the dust along the line of sight to the source and on the physical properties of the scattering dust particles. Halos around X-ray point sources have been used by several authors to infer that the scattering dust particles are fluffy in nature, consisting of aggregates of smaller refractory particles with vacuum occupying a significant fraction of their volume. The nature and morphology of interstellar dust particles has recently gained new importance, since fluffy, composite dust particles have been suggested as a possible solution to the interstellar carbon "crisis. " This crisis results from the discrepancy between the abundance of carbon in the interstellar medium available for creating dust and the significantly larger amount of carbon that must be in dust in order to account for the UV-optical interstellar extinction in the diffuse ISM. Previous studies of X-ray scattering have used the Rayleigh-Gans (RG) approximation to the differential scattering cross section to calculate halo properties. However, the validity of the RG approximation fails for energies below 1 keV. We use the exact Mie solution for the differential scattering cross section and find that, for these energies, the scattering becomes much less efficient than is predicted by the RG approximation. Furthermore, the effects of K and L shell absorption by atoms in the dust become important. The net effect is that the RG approximation systematically and substantially overestimates the intensity of the halo below 1 keV, relative to the Mie solution result. In particular, Mathis and coworkers used the weaker than expected halo intensity observed around Nova Cygni 1992 to conclude that interstellar dust must be fluffy. Using the Mie solution to the scattering intensity and including the effects of absorption, we find that, contrary to the conclusion of Mathis and coworkers, the halo around Nova Cygni 1992 does not require interstellar dust grains to be fluffy in nature and that the data are consistent with scattering from a mixture of bare refractory silicate and carbon grains as well.
Verifiable Mixing (Shuffling) of ElGamal Pairs

We give an improved presentation of the protocol first published in [23]. That paper contained some minor misprints, and was thin on formal proofs of correctness; both shortcomings are addressed in the current version. We also make some brief comparisons with, and criticisms of some more recent publications which build on the results presented in [23]. In particular, we point out that, in contrast to other protocols, the protocol of this paper is unconditionally sound.
Role of Fos-related antigen 1 in the progression and prognosis of ductal breast carcinoma

Logullo A F, Stiepcich M M Á, de Toledo Osório C A B, Nonogaki S, Pasini F S, Rocha R M, Soares F A & Brentani M M (2011) Histopathology 58, 617–625 Role of Fos‐related antigen 1 in the progression and prognosis of ductal breast carcinoma
CFD Simulation of Dry and Wet Pressure Drops and Flow Pattern in Catalytic Structured Packings

Type of packings and characteristics of their geometry can affect the flow behavior in the reactive distillation columns. KATAPAK SP is one the newest modular catalytic structured packings (MCSP) that has been used in the reactive distillation columns, recently. However, there is not any study on the hydrodynamics of this packing by using computational fluid dynamics. In the present work, a 3D VOF model was developed to evaluate dry and wet pressure drops of catalytic structured packings, MCSP-11 and 12. The module of MCSP is made of alternating vertical layers of structured packing sheets (Mellapak Plus) and catalyst bags. The goal of this paper is to illustrate the effect of geometry on the hydrodynamics and characterization of flow in the MCSP modules. Results showed that the mean relative errors for prediction of dry and wet pressure drops were 17% and 7% for MCSP-11 and 11% and 12% for MCSP-12, respectively. According to CFD results, pressure drop in closed channels was higher than that in open channels. The catalyst bags were simulated as porous media. The simulation led to determination of the liquid velocity distribution in the catalyst bags.
Piezo-actuated tunable diamond/AlN micro lenses

Tunable micro lenses based on boron-doped nanocrystalline diamond and aluminum nitride (AlN) thin films are investigated. It is demonstrated that such a material combination is advantageous for the fabrication of highly transparent, mechanically stable optical components capable to operate at high actuation frequencies. In addition, it is shown that radially segmented AlN piezo-actuators allow for free aspheric deformation of the lens surface. It enables the use of such tunable lenses either in wave front filters or for correction of aberrations induced in complex optical systems.
Keystroke dynamics for authentication in smartphone

When entering a PIN on the touch screen of smartphone, users have their unique patterns, which shows different time interval, strength, position, and usage angel. Using this user's pattern, it is possible to distinguish the imposter who knows the user's PIN, then the PIN verification can be enhanced in the smartphone environment. In this paper, we tested classifiers with five features that can be extracted from smartphone sensors. Also, we collected keystroke data for each user's posture, and compared the characteristics of the posture. We consider the importance of preprocessing and feature combinations.
Current Distance Relations for Fiber Stimulation With Pointsources

The following results are based on computer simulations and on activating function analysis. In the near field, denervated muscle fibers as well as nerve fibers with a sealed ending are easier to stimulate in the central region than with electrodes close to the end. When electrode-fiber distance is increased, the electrode location for optimal stimulation efficacy shifts from a central position to a region beyond the fiber end for cathodic stimulation and to a position above the terminating part of the fiber for anodic currents. The phenomenon becomes more pronounced with increasing distance between the electrode and fiber axis, because in the far field, the current-distance relation changes from quadratic to cubic, whereas stimulation at the fiber end obeys a rather constant quadratic law.
CXCL10 Decreases GP73 Expression in Hepatoma Cells at the Early Stage of Hepatitis C Virus (HCV) Infection

Golgi protein 73 (GP73), which is up-regulated in hepatocellular carcinoma (HCC), has recently been identified as a novel serum marker for HCC diagnosis. Several reports also noted the increased levels of GP73 expression in chronic liver disease in patients with acute hepatitis of various etiologies, chronic Hepatitis C virus (HCV) infection and alcoholic liver disease. The molecular mechanisms of GP73 expression in HCV related liver disease still need to be determined. In this study, we aimed to evaluate the effect of HCV infection on GP73 expression. GP73 was highly expressed in Huh7, Hep3B, 293T and HUVEC cells, and was low-expressed in HepG2 cells. HCV infection led to down-regulation of GP73 in Huh7 and HepG2/CD81 cells at the early stage of infection. CXCL10 decreased GP73 expression in Huh7 and HepG2 cells. Up-regulation of GP73 was noted in hepatocytes with cytopathic effect at advanced stage of HCV infection, and further research is needed to determine the unknown factors affecting GP73 expression. In conclusion, our study provided additional evidence for the roles of GP73 in liver disease.