Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of H19 Gene Regulatory Sequences in DNA-Based Therapy for Pancreatic Cancer

Pancreatic cancer is the eighth most common cause of death from cancer in the world, for which palliative treatments are not effective and frequently accompanied by severe side effects. We propose a DNA-based therapy for pancreatic cancer using a nonviral vector, expressing the diphtheria toxin A chain under the control of the H19 gene regulatory sequences. The H19 gene is an oncofetal RNA expressed during embryo development and in several types of cancer. We tested the expression of H19 gene in patients, and found that 65% of human pancreatic tumors analyzed showed moderated to strong expression of the gene. In vitro experiments showed that the vector was effective in reducing Luciferase protein activity on pancreatic carcinoma cell lines. In vivo experiment results revealed tumor growth arrest in different animal models for pancreatic cancer. Differences in tumor size between control and treated groups reached a 75% in the heterotopic model (P = .037) and 50% in the orthotopic model (P = .007). In addition, no visible metastases were found in the treated group of the orthotopic model. These results indicate that the treatment with the vector DTA-H19 might be a viable new therapeutic option for patients with unresectable pancreatic cancer.
Image denoising using regularized Butterworth wavelet frames

We present an efficient algorithm for image restoration from highly noised originals. The algorithm is based on diverse library of tight and semi-tight wavelet frames. Unlike majority of current denoising methods, which threshold the transform coefficients, our algorithm performs direct and inverse multiscale transforms using properly modified frame filters. No thresholding is applied. The processing is linear. The algorithm is fast and can be implemented in real time. It depends on one numerical parameter, which is estimated from the noise level.
User location forecasting at points of interest

Predicting the location of a mobile user in the near future can be used for a very large number of user-centered or crowd-centered ubiquitous applications. It is convenient for the discussion to think in terms of discrete locations driven by Points of Interest (POI) instead of absolute positions. We postulate that POI sequences are Markovian once the data is clustered by day of the week and time of the day. To prove our hypothesis we used a public dataset, used in a previous work [16]. In that paper the authors were able to predict the location of a user with 90% to 70% accuracy in five minutes and one hour time windows, respectively. With our approach, using Hidden Markov Models, we are able to predict the next POIs within seven hours without significant accuracy decrease. This result enables a large number of potential applications where the aggregate data of a single users conform the behavior of the crowd.
EJECTA KNOT FLICKERING, MASS ABLATION, AND FRAGMENTATION IN CASSIOPEIA A

Ejecta knot flickering, ablation tails, and fragmentation are expected signatures associated with the gradual dissolution of high-velocity supernova (SN) ejecta caused by their passage through an inhomogeneous circumstellar medium or interstellar medium (ISM). Such phenomena mark the initial stages of the gradual merger of SN ejecta with and the enrichment of the surrounding ISM. Here we report on an investigation of this process through changes in the optical flux and morphology of several high-velocity ejecta knots located in the outskirts of the young core-collapse SN remnant Cassiopeia A using Hubble Space Telescope images. Examination of WFPC2 F675W and combined ACS F625W + F775W images taken between 1999 June and 2004 December of several dozen debris fragments in the remnant's northeast ejecta stream and along the remnant's eastern limb reveal substantial emission variations (“flickering”) over timescales as short as nine months. Such widespread and rapid variability indicates knot scale lengths ≃ 1015 cm and a highly inhomogeneous surrounding medium. We also identify a small percentage of ejecta knots located all around the remnant's outer periphery which show trailing emissions typically 0. ″2–0. ″7 in length aligned along the knot's direction of motion suggestive of knot ablation tails. We discuss the nature of these trailing emissions as they pertain to ablation cooling, knot disruption, and fragmentation, and draw comparisons to the emission “strings” seen in η Car. Finally, we identify several tight clusters of small ejecta knots which resemble models of shock-induced fragmentation of larger SN ejecta knots caused by a high-velocity interaction with a lower density ambient medium.
Two-hand gesture recognition using coupled switching linear model

We present a method of coupling multiple switching linear models. The coupled switching linear model is an interactive process of two switching linear models. Coupling is given through causal influence between their hidden discrete states. The parameters of this model are learned via EM algorithm. Tracking is performed through the coupled-forward algorithm based on Kalman filtering and a collapsing method. A model with maximum likelihood is selected out of a few learned models during tracking. We demonstrate the application of the proposed model to tracking and recognizing two-hand gestures.
Text Readability Classification of Textbooks of a Low-Resource Language

There are many languages considered to be low-density languages, either because the population speaking the language is not very large, or because insufficient digitized text material is available in the language even though millions of people speak the language. Bangla is one of the latter ones. Readability classification is an important Natural Language Processing (NLP) application that can be used to judge the quality of documents and assist writers to locate possible problems. This paper presents a readability classifier of Bangla textbook documents based on information-theoretic and lexical features. The features proposed in this paper result in an F-score that is 50% higher than that for traditional readability formulas.
Keefektifan Model STAD dan Direct Learning Berdasarkan Prestasi dan Minat Belajar Matematika Materi Kesebangunan Bangun Datar

Penelitian ini bertujuan untuk: (1) mendeskripsikan keefektifan pembelajaran kooperatif model Student Teams Achievement Division (STAD) dengan pembelajaran langsung (direct learning) pada materi kesebangunan bangun datar ditinjau dari prestasi dan minat belajar, (2) membandingkan keefektifan antara pembelajaran kooperatif model STAD dan direct learning. Penelitian ini merupakan penelitian eksperimen semu. Populasi penelitian terdiri dari empat kelas, sedangkan sampel terdiri dari dua kelas yang dipilih secara acak dengan siswa sebanyak 64 siswa. Instrumen penelitian adalah instrumen tes prestasi dan angket minat belajar. Analisis data (statistik inferensial) meliputi: (1) uji t one sample, (2) analisis multivariat dengan Hotelling’s Trace, dan (3) uji lanjut dengan Equal Variances assumed dengan taraf signifikansi 5%. Hasil penelitian menunjukkan bahwa: (1) pembelajaran model STAD dan direct learning efektif ditinjau dari prestasi dan minat belajar matematika siswa dan (2) pembelajaran model STAD lebih efektif daripada direct learning ditinjau dari minat belajar matematika siswa, tetapi tidak lebih efektif bila ditinjau dari prestasi belajar matematika siswa.Kata kunci: Student Teams Achievement Division (STAD), pembelajaran langsung (direct learning), prestasi, dan minat belajar matematika siswa. The Effectiveness of the STAD and Direct Learning Models in Terms of Learning Achievement and Interest in Mathematics for Topic of Plane Figure Similarity AbstractThe aims of this research were to describe the effectiveness of the Student Teams Achievement Division (STAD) cooperative learning model and direct learning in mathematics learning for topic of plane figure similarity in terms of learning achievement and interest in mathematics and compare both of them. This was a quasi-experimental study. The research population comprised four classes. The research sample consisted of two classes, which were randomly selected. The research instruments were an achievement test and a learning interest questionnaire. The data analysis included: (1) one sample t-test, (2) multivariate analysis using Hotelling’s Trace, and (3) a post hoc test using Equal Variances Assumed with significance level of 5%. The results of the study showed that: (1) the STAD and direct learning models were effective in terms of the students’ mathematics learning achievement and interest and (2) the STAD learning model is more effective than direct learning model in terms of the students’ mathematics learning interest, but it wasn’t as effective based on the students’ mathematics learning achievement. Keywords: STAD learning model, direct learning, students’ mathematics learning achievement and interest
Experimental results for standoff detection of concealed body-worn explosives using millimeter-wave radar and limited view ISAR processing

In the increasingly important problem of identifying suicide bombers wearing explosives concealed under clothing, it is essential to detect suspicious individuals at a distance. Current systems employ multiple sensors to determine the presence of explosives on people, including observing and following individuals, identifying explosive residues or heat signatures on the outer surface of their clothing, or by characterizing explosives using penetrating X-rays or terahertz wave radar. At present, radar is the only modality that can penetrate and sense beneath clothing at a distance of 10 to 50 meters without causing physical harm. Unfortunately, current radar systems require impractically large synthetic apertures to effectively distinguish people wearing concealed body-worn improvised explosive devices from innocent individuals. We explore these limitations and propose strategies to maximize detection with limited apertures.
Stress induction of the mammalian GRP78/BiP protein gene: in vivo genomic footprinting and identification of p70CORE from human nuclear extract as a DNA-binding component specific to the stress regulatory element

GRP78, also known as BiP, is one of the better-characterized molecular chaperones. It has been implicated in protein folding and also calcium sequestration in the endoplasmic reticulum. When the cells are subjected to endoplasmic reticulum stress, in particular the depletion of stored calcium and/or the accumulation of abnormal proteins, the rate of transcription of grp78 is enhanced. Previous studies have shown that the core region of the rat grp78 promoter (-170 to -135), which is 95% conserved with the human grp78 core (-133 to -98), is one of the key regulatory elements. Using ligation-mediated PCR, we have found that there are specific changes in factor occupancy after stress induction and the major changes occur within a cluster of bases located in the 3' half of the grp core, whereas other regulatory elements are constitutively occupied. This inducible binding to the 3' half of the human grp78 core region is observed under diverse stress signals, suggesting a common mechanism for the grp stress response. Nonetheless, the lack of constitutive in vivo protection at this region is not due to the absence of a binding factor in nuclear extracts. Using in vitro gel mobility shift assays, we detected a constitutive binding activity which exhibits specificity and affinity to the stress-inducible region. Through sodium dodecyl sulfate-polyacrylamide gel electrophoresis size fractionation and renaturation analysis, the activity is found in polypeptides with molecular sizes of 65 to 75 kDa. After a three-step purification scheme including core affinity column chromatography, we purified p70CORE, which is about 70 kDa in its monomeric form. The purified p70CORE is sufficient to form a complex specific to the stress-inducible region.
Performance improvements from imagery: evidence that internal visual imagery is superior to external visual imagery for slalom performance

We report three experiments investigating the hypothesis that use of internal visual imagery (IVI) would be superior to external visual imagery (EVI) for the performance of different slalom-based motor tasks. In Experiment 1, three groups of participants (IVI, EVI, and a control group) performed a driving-simulation slalom task. The IVI group achieved significantly quicker lap times than EVI and the control group. In Experiment 2, participants performed a downhill running slalom task under both IVI and EVI conditions. Performance was again quickest in the IVI compared to EVI condition, with no differences in accuracy. Experiment 3 used the same group design as Experiment 1, but with participants performing a downhill ski-slalom task. Results revealed the IVI group to be significantly more accurate than the control group, with no significant differences in time taken to complete the task. These results support the beneficial effects of IVI for slalom-based tasks, and significantly advances our knowledge related to the differential effects of visual imagery perspectives on motor performance.
A Cross-Layer Approach for an Efficient Delivery of TCP/RTP-Based Multimedia Applications in Heterogeneous Wireless Networks

Recent trends in the telecommunication industry have been moving toward the development of ubiquitous information systems, where the provision of a plethora of advanced multimedia services should be possible, regardless of time and space limitations. An efficient and seamless delivery of multimedia services over various types of wireless networks is still a challenging task. The underlying difficulty consists of the disparity in the bandwidth availability over each network type. Indeed, the fundamental challenge upon a handoff phenomenon in a heterogeneous wireless network consists of an efficient probing of the bandwidth availability of the new network, followed by a prompt adjustment of the data delivery rate. This paper presents a cross-layer approach that involves five layers, namely, physical, data link, application, network, and transport layers. The three former layers are used to anticipate the handoff occurrence and to locate the new point of attachment to the network. Based on their feedback, the transport layer is used then to probe the resources of the new network using low-priority dummy packets. Being the most widely used protocol for multimedia delivery, this paper addresses multimedia applications based on the Transmission Control Protocol (TCP) and the Real-time Transport Protocol (RTP). The design of the whole cross-layer architecture is discussed, and enhancements to the two protocols are proposed. The performance of the enhanced TCP and the RTP are evaluated and compared against existing schemes through extensive simulations. The obtained results are encouraging and promising for the delivery of multimedia services in heterogeneous wireless networks.
Feature Detection for Vehicle Localization in Urban Environments Using a Multilayer LIDAR

Localization is an important component of autonomous vehicles, as it enables the accomplishment of tasks, such as path planning and navigation. Although vehicle position can be obtained by GNSS devices, they are susceptible to errors and satellite signal unavailability in urban scenarios. Several map-aided localization solution methods have been proposed in the literature, but mostly for indoor environments. Maps used for localization store relevant environmental features that are extracted by a detection method. However, many feature detection methods do not consider the presence of dynamic obstacles or occlusions in the environment, which can impair the localization performance. In order to detect curbs even in occluding scenes, we developed a method based on ring compression analysis and least trimmed squares. For road marking detection, we developed a modified version of the Otsu thresholding method to segment road painting from road surfaces. Finally, the feature detection methods were integrated with a Monte Carlo localization method to estimate the vehicle position. Experimental tests in urban streets have been used to validate the proposed approach with favorable results.
Medusa: A Parallel Graph Processing System on Graphics Processors

Medusa is a parallel graph processing system on graphics processors (GPUs). The core design of Medusa is to enable developers to leverage the massive parallelism and other hardware features of GPUs by writing sequential C/C++ code for a small set of APIs. This simplifies the implementation of parallel graph processing on the GPU. The runtime system of Medusa automatically executes the user-defined APIs in parallel on the GPU, with a series of optimizations based on the architecture features of GPUs and characteristics of graph applications. In this paper, we present an overview of the Medusa system and a case study of adopting Medusa to a research project on social network simulations. With Medusa, users without GPU programming experiencecan quickly implement their graph operations on the GPU, which accelerates the discovery and findings of domain-specific applications.
A novel hybrid method using Adaptive Wiener Filter and Example-based Approaches for aerial image super-resolution

A novel hybrid method is proposed for aerial image super-resolution in which the output of the Adaptive Wiener Filter (AWF) based super resolution technique is further enhanced using Example-based Super-Resolution (EBSR). While AWF method gives a reasonable result measured in terms of perceptual quality, it has a disadvantage of blurring the image on account of the weighted averaging. Introduction of EBSR compensates for the loss of high frequency content and results in sharpening the edges. This paper demonstrates the effectiveness of the hybrid approach in improving the overall performance.
Methodical study of nitrous oxide eddy covariance measurements using quantum cascade laser spectrometery over a Swiss forest

Abstract. Nitrous oxide fluxes were measured at the Lageren CarboEurope IP flux site over the multi-species mixed forest dominated by European beech and Norway spruce. Measurements were carried out during a four-week period in October–November 2005 during leaf senescence. Fluxes were measured with a standard ultrasonic anemometer in combination with a quantum cascade laser absorption spectrometer that measured N2O, CO2, and H2O mixing ratios simultaneously at 5 Hz time resolution. To distinguish insignificant fluxes from significant ones it is proposed to use a new approach based on the significance of the correlation coefficient between vertical wind speed and mixing ratio fluctuations. This procedure eliminated roughly 56% of our half-hourly fluxes. Based on the remaining, quality checked N2O fluxes we quantified the mean efflux at 0.8±0.4 μmol m−2 h−1 (mean ± standard error). Most of the contribution to the N2O flux occurred during a 6.5-h period starting 4.5 h before each precipitation event. No relation with precipitation amount could be found. Visibility data representing fog density and duration at the site indicate that wetting of the canopy may have as strong an effect on N2O effluxes as does below-ground microbial activity. It is speculated that above-ground N2O production from the senescing leaves at high moisture (fog, drizzle, onset of precipitation event) may be responsible for part of the measured flux.
Durational modelling for improved connected digit recognition

A durational modelling technique is proposed for CDHMM-based connected digit recognition. This reduces the insertion error rate, which is typically the most frequent recognition error observed when no grammar constraint is applied. Insertion errors can be attributed in part to the acknowledged weakness of the acoustic models for accurate temporal modeling of speech signals. Two forms of durational model are investigated: an expanded-state model and an explicit model. Both forms of model significantly reduce the number of insertion errors and hence the digit string error rate. A modification to the explicit model which also accounts for speaking rate is described.
Biomarkers of major depressive disorder : a study of the interaction of genetic, neuroimaging and endocrine factors, and the effects of childhood adversity, in major depressive disorder

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A Rare Cause of Colonic Obstruction “Colonic Intussusception”: Report of Two Cases

Colocolic intussusceptions are rare clinical entities in adults and almost always caused by a leading lesion which often warrants resection. Mostly being malignant, the leading lesions are rarely benign lesions where intraluminal lipomas are the most frequent among them. Most adult intussusceptions require surgical resection owing to two major reasons: common presence of a leading lesion and significantly high risk of malignancy—reaching as high as 65% regardless of the anatomic site—of the leading lesion. Resection of the affected segment is usually the treatment of choice, since preoperative diagnosis of the lesion is usually ineffective and most leading lesions are malignant. This paper represents two cases of adult colocolic intussusception caused by intraluminal lipomas with a brief review of the literature.
Distribution Metric Driven Adaptive Random Testing

Adaptive random testing (ART) was developed to enhance the failure detection capability of random testing. The basic principle of ART is to enforce random test cases evenly spread inside the input domain. Various distribution metrics have been used to measure different aspects of the evenness of test case distribution. As expected, it has been observed that the failure detection capability of an ART algorithm is related to how evenly test cases are distributed. Motivated by such an observation, we propose a new family of ART algorithms, namely distribution metric driven ART, in which, distribution metrics are key drivers for evenly spreading test cases inside ART. Out study uncovers several interesting results and shows that the new algorithms can spread test cases more evenly, and also have better failure detection capabilities.
Frequency reconfigurable patch antenna using PIN diode at X-band

In this paper the design of an X-band frequency reconfigurable patch antenna has been demonstrated using PIN diode. A square slot has been introduced in order to realize PIN diode effect in antenna parameters. The tuning of frequency is realized by changing its effective electrical length, which is controlled by different mode of the PIN diode by applying different bias voltages across it along the slot of the antenna. An annular slot rectangular patch antenna is used and a gap of 2mm is used to attach PIN diode. When the PIN diode is forward biased i.e gap is closed by PIN diode and current will flow along the outer ring. ±60 MHz (1.34 %) tuning of frequency has been obtained by applying the bias voltage of 3 volt. The structure has been simulated in ADS software. Simulated and measured performances are presented. Results are used to demonstrate that there is good agreement between the simulated and measured results. The match between simulation and measured results suggests that proposed candidate can be used as a frequency reconfigurable antenna.