Miracle-dz/UniFAR-FTUs huggingface dataset:
Cutaneous Squamous Cell Carcinoma of the Head and Neck

Cutaneous squamous cell carcinoma of the head and neck is an epidemic that reaches all parts of the world. Making the diagnosis relies on the acumen of the clinician and pathologist. Various pathologic subtypes exist and differ in histology and prognosis. High-risk tumors need aggressive treatment and vigilant surveillance to monitor for recurrence. Large tumors, deep tissue invasion, perineural involvement, recurrence, location in high-risk areas, and immunosuppression are implicated in worsening prognosis. Surgery is the mainstay of treatment with adjuvant radiation therapy as needed for aggressive tumors; however, other modalities are potentially useful for low-risk lesions. The use of Mohs surgery has become increasingly useful and has shown high success rates. Involvement of parotid and neck lymph nodes significantly affects outcomes and the physician should be comfortable with management of this complex disease. This paper examines the diagnosis, pathology, clinical course, and treatment options for cutaneous squamous cell carcinoma of the head and neck.
A faster optimal register allocator

Recently researchers have proposed modeling register allocation as an integer linear programming (IP) problem and solving it optimally for general purpose processors and for dedicated embedded systems. Compared with traditional graph-coloring approaches, the IP-based allocators can improve a program's performance. However the solution times are much slower This paper presents an IP-based optimal register allocator which is much faster than previous work. We present several local and global reduction techniques to identify locations in a program's control-flow graph where spill decisions and register deallocation decisions are unnecessary for optimal register allocation. We propose a hierarchical reduction approach to efficiently remove the corresponding redundant decisions and constraints from the IP model. This allocator is built into the Gnu C Compiler and is evaluated experimentally using the SPEC92INT benchmarks. The results show that the improved IP model is much simpler The number of constraints produced is almost linear with the function size. The optimal allocation time is much faster with a speedup factor of about 150 for hard allocation problems.
Decision combining in relay networks

We consider non-coherent detection of M-ary FSK modulated signals transmitted over a slow, Rayleigh fading channel in a wireless relay network. The network consists of a single source-destination pair and a number of relays (L), which employ cooperative diversity. Performances of a counting rule and square law combiner are studied. We derive closed form expressions for probabilities of error for equal relay channel average SNR. For unequal relay channel SNRs, we resort to Monte Carlo simulations to estimate the error probabilities. We examine different combinations of M and L for a range of average SNR values. Although the square law combiner outperforms the counting rule for equal and small average SNRs, the loss in performance is not high. Simplicity of counting rule may be advantageous in these cases.
Hubungan Antara Optimism dan Academic Adjustment Mahasiswa Semester Tiga Fakultas Psikologi di Universitas "X" Bandung

Penelitian ini dilaksanakan untuk mengetahui hubungan antara optimism dan academic adjustment pada mahasiswa semester awal Fakultas Psikologi di Universitas “X” Bandung. Subjek dalam penelitian ini adalah mahasiswa Fakultas Psikologi yang berjumlah 129 irang. Rancangan dalam penelitian ini menggunakan metode korelasional. Alat ukur optimism yang digunakan dalam penelitian ini merupakan modifikasi peneliti dari alat ukur oleh E.P. Seligman (1990) yang telah diterjemahkan oleh Drs. Paulus Hidajat Prasetya (1996), dan alat ukur academic adjustment disusun oleh peneliti. Validitas alat ukur optimism diuji dengan korelasi point-biserial dengan bantuan excel 2013 (berkisar antara 0.3-0.65) dan academic adjustment dengan korelasi Rank Spearman dengan bantuan SPSS 24.0 for Windows (berkisar antara 0.3-0.62). Reliabilitas alat ukur optimism diuji dengan Kuder-20 dengan bantuan excel 2013 (berkisar antara 0.3-0.65) dan academic adjustment dengan Alpha Cronbach dengan bantuan SPSS 24.0 for Windows (reliabilitas 0.874). Berdasarkan pengolahan data dengan uji korelasi Rank Spearman, terlihat hubungan yang cukup erat antara optimism dan academic adjustment. Kemudian, dari ketiga dimensi optimism, hubungan dimensi permanence dengan academic adjustment lebih erat dari pada hubungan kedua dimensi lainnya. Peneliti mengajukan saran agar dilakukan penelitian lebih lanjut mengenai peran optimism terhadap academic adjustment pada mahasiswa Fakultas Psikologi. Bagi pihak fakultas, hasil penelitian ini dapat digunakan sebagai bahan pertimbangan dalam menyusun pelatihan yang dapat meningkatkan optimism dan academic adjustment mahasiswa.
Fabrication and Pilot In Vivo Study of a Collagen-BDDGE-Elastin Core-Shell Scaffold for Tendon Regeneration

The development of bio-devices for complete regeneration of ligament and tendon tissues is presently one of the biggest challenges in tissue engineering. Such device must simultaneously possess optimal mechanical performance, suitable porous structure, and biocompatible microenvironment. This study proposes a novel collagen-BDDGE-elastin (CBE)-based device for tendon tissue engineering, by the combination of two different modules: (i) a load-bearing, non-porous, “core scaffold” developed by braiding CBE membranes fabricated via an evaporative process and (ii) a hollow, highly porous, “shell scaffold” obtained by uniaxial freezing followed by freeze-drying of CBE suspension, designed to function as a physical guide and reservoir of cells to promote the regenerative process. Both core and shell materials demonstrated good cytocompatibility in vitro, and notably, the porous shell architecture directed cell alignment and population within the sample. Finally, a prototype of the core module was implanted in a rat tendon lesion model, and histological analysis demonstrated its safety, biocompatibility, and ability to induce tendon regeneration. Overall, our results indicate that such device may have the potential to support and induce in situ tendon regeneration.
A learning-based approach for Romanian syllabification and stress assignment

This paper tackles the Romanian syllabification and stress assignment problems, and proposes an efficient machine learning based solution. We show that by designing the appropriate feature sets for each specific problem, learning algorithms achieve satisfactory accuracy rates for both problems (~92% for syllabification, ~85% for stress assignment), even for relatively small training set sizes. We have found that unigram-based features are powerful enough to characterize these problems, and therefore the introduction of bi-gram or tri-gram features (often utilized in syllabification problems for other languages) is unnecessary.
Long-Term Gains from Longer School Days

ABSTRACT This work examines whether additional time in elementary and secondary school affects economic well-being in adulthood. We leverage cross-municipality and cross-cohort variation in a reform that increased the Chilean school day by 30 percent between 1997 and 2010 and find that full-day schooling increased educational attainment, delayed childbearing, and increased earnings when students reached young adulthood. These findings are consistent with a human capital channel and demonstrate that large-scale investments in public education can yield long-term economic benefits.
Examining the Robustness of the Inflation and Growth Relationship

Using Bayesian Model Averaging, we examine whether inflation's effects on economic growth are robust to model uncertainty across numerous specifications. Cross-sectional data provide little evidence of a robust inflation-growth relationship, even after allowing for non-linear effects. Panel data with fixed effects suggest inflation is one of the more robust variables affecting growth, and non-linear results suggest that high inflation observations drive the results. However, this robustness is lost when estimation is carried out with instrumental variables.
A Novel Low Pass Filter Using Elliptic Shape Defected Ground Sstructure

This paper presents a novel elliptic shape defected ground structure (DGS) for low pass filter (LPF) applications. An equivalent RLC circuit model is presented and its corresponding parameters are also extracted from the measured S-parameters. The filter presents the advantages of compact size, high selectivity; low insertion loss and high out-band suppression from 5.15 GHz to 10 GHz below −31 dB. Good agreement with response of equivalent circuit, electromagnetic simulation, and measurement is demonstrated
Classification of EEG signals in four groups, including healthy subjects with open/closed eyes and epilepsy subjects with/without seizure by PSD estimate (using the multitaper method) and ANN

Electroencephalography (EEG) analysis by physicians is intricate, time consuming and needs to experience. Therefore automated systems for EEG analysis and classification are able to help physician. EEG signal in the field of time is raw and complex so it's not suitable for automated system. Therefore appropriate features of EEG signal becomes extraction using signal processing methods (in this paper used Thomson multi taper method's (MTM)), then these features becomes classification by ANN. Also we have to correct the ANN outputs by a threshold function. In this study, EEG signals are classified in three groups (including epileptic patients with seizure or without seizure and healthy volunteers) with 98.02% accuracy and in two groups (healthy with closed or open eyes) with 97.7% accuracy.
Treatment of Attention-Deficit/Hyperactivity Disorder: Overview of the Evidence

The American Academy of Pediatrics' Committee on Quality Improvement, Subcommittee on Attention-Deficit/Hyperactivity Disorder, reviewed and analyzed the current literature for the purpose of developing an evidence-based clinical practice guideline for the treatment of the school-aged child with attention-deficit/hyperactivity disorder (ADHD). This review included several key reports, including an evidence review from the McMaster Evidence-Based Practice Center (supported by the Agency for Healthcare Research and Quality), a report from the Canadian Coordinating Office for Health Technology Assessment, the Multimodal Treatment for ADHD comparative clinical trial (supported by the National Institute of Mental Health), and supplemental reviews conducted by the subcommittee. These reviews provided substantial information about different treatments for ADHD and their efficacy in improving certain characteristics or outcomes for children with ADHD as well as adverse effects and benefits of multiple modes of treatment compared with single modes (eg, medication or behavior therapies alone). The reviews also compared the effects of different medications. Other evidence documents the long-term nature of ADHD in children and its classification as a chronic condition, meriting the application of general concepts of chronic-condition management, including an individual treatment plan with a focus on ongoing parent and child education, management, and monitoring. The evidence strongly supports the use of stimulant medications for treating the core symptoms of children with ADHD and, to a lesser degree, for improving functioning. Behavior therapy alone has only limited effect on symptoms or functioning of children with ADHD, although combining behavior therapy with medication seems to improve functioning and may decrease the amount of (stimulant) medication needed. Comparison among stimulants (mainly methylphenidate and amphetamines) did not indicate that 1 class outperformed the other.
An original approach for processing public open data with MapReduce: A case study

Nowadays, many governments and states are involved in an opening strategy of their public data. However, the volume of these opened data is constantly increasing, and will reach in the near future limitations of current treatment and storage capacity. On the other hand, the MapReduce paradigm is one of the most used parallel programming models. With a master-slave architecture, it allows parallel processing of very large data sets. In this paper, we propose a parallel approach based on Mapreduce to process public open data. Applied, as a case study, to the official data sets from the French Ministry of Communication. We implement a parallel algorithm as a solution to define a ranking of national museums and galleries according to the accessibility degrees for people with disabilities. We studied the feasibility of our approach in two main parts: The performance in terms of execution time, and, the visualization of the obtained results in order to integrate them into solutions such as geographic BI. This work can be applied to other cases with very large data sets.
Outlier Detection Algorithms in Data Mining

Outlier is defined as an observation that deviates too much from other observations. The identification of outliers can lead to the discovery of useful and meaningful knowledge. Outlier detection has been extensively studied in the past decades. However, most existing research focuses on the algorithm based on special background, compared with outlier detection approach is still rare. This paper mainly discusses and compares approach of different outlier detection from data mining perspective, which can be categorized into two categories: classic outlier approach and spatial outlier approach. The classic outlier approach analyzes outlier based on transaction dataset, which can be grouped into statistical-based approach, distance-based approach, deviation-based approach, density-based approach. The spatial outlier approach analyzes outlier based on spatial dataset that non-spatial and spatial data are significantly different from transaction data, which can be grouped into space-based approach and graph-based approach. Finally, the paper concludes some advances in outlier detection recently.
Exact Expressions for the Pericenter Precession Caused by Some Dark Matter Distributions and Constraints on Them from Orbital Motions in the Solar System, in the Double Pulsar and in the Galactic Center

We analytically calculate the secular precession of the pericenter of a test particle orbiting a central body surrounded by a continuous distribution of Dark Matter (DM) by using some commonly adopted spherically symmetric density profiles for it. We obtain exact expressions without resorting to a-priori simplifying assumptions on the orbital geometry of the test particle. Our formulas allow us to put constraints on the parameters of the DM distributions considered in several local astronomical and astrophysical scenarios, such as the Sun's planetary system, the double pulsar, and the stellar system around the supermassive black hole in Sgr A∗, all characterized by a wide variety of orbital configuratio ns. As far as our Solar System is concerned, latest determinations of the supplementary perihelion precessions ˙ with the EPM2011 ephemerides and the common power-law DM density profile ρDM(r) = ρ0r−γ λγ yield 5 × 103 GeV cm−3 (γ = 0) ≤ ρ0 ≤ 8 × 103 GeV cm−3 (γ = 4), corresponding to 8.9 × 10−21 g cm−3 ≤ ρ0 ≤ 1.4 × 10−20 g cm−3, at the Saturn's distance. From the periastron of the pulsar PSR J0737-3039A and the same power-low DM density, one has 1.7 × 1016 GeV cm−3 (γ = 0) ≤ ρ0 ≤ 2 × 1016 (γ = 4) GeV cm−3, corresponding to 3.0 × 10−8 g cm−3 ≤ ρ0 ≤ 3.6 × 10−8 g cm−3. The perinigricon of the S0-2 star in Sgr A∗ and the power-law DM model give 1.2 × 1013 GeV cm−3 (γ = 0) ≤ ρ0 ≤ 1 × 1016 (γ = 4, λ = rmin) GeV cm−3, corresponding to 2.1 × 10−11 g cm−3 ≤ ρ0 ≤ 1.8 × 10−8 g cm−3.
Fuzzy backstepping control for dual-arm cooperative robot grasp

In this paper, a fuzzy backstepping control algorithm (FBC) for dual-arm cooperative robot is proposed to implement a grasp task. Firstly, the dual-arm cooperative dynamic model including dual-arm robot dynamic and objective dynamic is established. Secondly, The FBC is aim to eliminate the nonlinear uncertain and improve the performance of position-tracking of the end-effecter. Third, the hybrid system based on force and position control is proposed to complete the dual-arm cooperative grasp. Moreover, the Lypunova theory is applied to guarantee the stability of the closed-loop system of the dual-arm robot. Finally, the effectiveness of the proposed algorithm and theory is demonstrated by the simulation on the simulink and experiment conducted on the humanoid robot.
Cross-Curricular Literacy: Writing for Learning in a Science Program

Teacher educator and researcher Peterson works with eighth-grade science teacher, Rochwerger, who believes that writing is a learning tool that will enable her students to become scientifically literate. Here, we see this belief played out through an action research project that found students using a genre of their choice to write about what they had learned during hands-on activities in the classroom, and analyzing a science fiction story for scientific principles. The authors conclude with a list of recommendations for teachers who would like to teach writing using content area topics or who would like to collaborate with science teachers in their schools.
ZVZCS Full Bridge Dc-Dc Converter with Reduced Circulating Loss and Filter Requirement

A new ZVZCS full bridge converter with phase-shift control is proposed to reduce the circulating loss in primary side and the voltage stress in secondary side. Using a coupled winding of the filter inductor, two auxiliary voltage sources are generated to reset the primary current at circulating interval. An auxiliary clamp diode is utilized to clamp the voltage spike across the rectifier diode, which releases the voltage stress for rectifier diode. Therefore low break down voltage diodes could be used to reduce the conducting loss and the reverse recovery loss. Also the filter requirements are lowered due to the auxiliary voltage sources. A prototype is built up to verify the theoretical analysis.
Analysis of Bit-Split Languages for Packet Scanning and Experiments with Wildcard Matching

Monitoring traffic payloads to detect the occurrence of suspicious patterns has proven to be a useful and necessary tool for network security. Bit-splitting breaks the problem of monitoring payloads to detect such patterns into several parallel components, each of which searches for a particular bit pattern. We analyze bit-splitting as applied to Aho-Corasick style string matching and present a formal treatment of bit-slicing to prove correctness and to provide bounds on the NFA to DFA conversion of the Aho-Corasick type machine used for bit-splitting. The problem can be viewed as the recovery of a special class of regular languages over product alphabets from a collection of homomorphic images. Furthermore, in an attempt to extend the flexibility and applicability of the original bit-splitting algorithm, we explore the expressiveness and limitations of bit-slicing with respect to wildcard matching applications.
Robopal: Modeling Role Transitions in Human-Robot Interaction

We have developed a new communication robot, Robopal, which is an indoor/outdoor robot for use in human-robot interaction research in the context of daily life. Robopal's intended applications involve leading and/or following a human to a destination. Preliminary experiments have been conducted to study nonverbal cues associated with leading and following behavior, and it has been observed that some behaviors, such as glancing towards the leader or follower, appear to be role-dependent. A system for representing these behaviors with a state transition model is described, based on four kinds of interaction roles: directive, responsive, collaborative, and independent. It is proposed that behavior modeling can be simplified by using this system to represent changes in the roles the robot and human play in an interaction, and by associating appropriate behaviors to each role
Podocyte-Specific Overexpression of Wild Type or Mutant Trpc6 in Mice Is Sufficient to Cause Glomerular Disease

Mutations in the TRPC6 calcium channel (Transient receptor potential channel 6) gene have been associated with familiar forms of Focal and Segmental Glomerulosclerosis (FSGS) affecting children and adults. In addition, acquired glomerular diseases are associated with increased expression levels of TRPC6. However, the exact role of TRPC6 in the pathogenesis of FSGS remains to be elucidated. In this work we describe the generation and phenotypic characterization of three different transgenic mouse lines with podocyte-specific overexpression of the wild type or any of two mutant forms of Trpc6 (P111Q and E896K) previously related to FSGS. Consistent with the human phenotype a non-nephrotic range of albuminuria was detectable in almost all transgenic lines. The histological analysis demonstrated that the transgenic mice developed a kidney disease similar to human FSGS. Differences of 2–3 folds in the presence of glomerular lesions were found between the non transgenic and transgenic mice expressing Trpc6 in its wild type or mutant forms specifically in podocytes. Electron microscopy of glomerulus from transgenic mice showed extensive podocyte foot process effacement. We conclude that overexpression of Trpc6 (wild type or mutated) in podocytes is sufficient to cause a kidney disease consistent with FSGS. Our results contribute to reinforce the central role of podocytes in the etiology of FSGS. These mice constitute an important new model in which to study future therapies and outcomes of this complex disease.
Sensitivity of the eigenfunctions and the level curvature distribution in quantum billiards

In searching for the manifestations of the sensitivity of the eigenfunctions in quantum billiards (with Dirichlet boundary conditions) with respect to the boundary data (the normal derivative), we have performed instead various numerical tests for the Robnik billiard (a quadratic conformal map of the unit disk) for 600 shape parameter values, where we have looked at the sensitivity of the energy levels with respect to the shape parameter. We show the energy level flow diagrams for three stretches of fifty consecutive (odd) eigenstates, each with index 1000 to 2000. In particular, we have calculated the (unfolded and normalized) level curvature distribution and found that it continuously changes from a delta distribution for the integrable case (circle) to a broad distribution in the classically ergodic regime. For some shape parameters the agreement with the GOE von Oppen formula is very good, whereas we have also cases where the deviation from GOE is significant and of physical origin. In the intermediate case of mixed classical dynamics we have a semiclassical formula in the spirit of the Berry - Robnik (1984) surmise. Here the agreement with theory is not good, partially due to the localization phenomena which are expected to disappear in the semiclassical limit. We stress that even for classically ergodic systems there is no global universality for the curvature distribution, not even in the semiclassical limit.