Miracle-dz/UniFAR-FTUs huggingface dataset:
Deposition of Variable Bead Diameter Arrays by Self-Focusing Electrohydrodynamic Jets

Electrohydrodynamic (EHD) processes were used for direct writing of bead arrays with controllable bead sizes. Experiments were conducted to align layers of bead-on-string structures in an effort to create three-dimensional patterns. The results show that the jet focuses on previously deposited droplets allowing for the selective deposition of material over already deposited patterns. Jet attraction to already deposited solutions on the substrate is attributed to the charge transport at the liquid ink–metal collector interface and the dielectric properties of the water/poly(ethylene oxide) (PEO) solution under an electric field. The deposition process consists of three steps: (1) deposition of a layer of bead-on-string structures, (2) addition of extra volume to the beads by subsequent passes of the jet, and (3) evaporation of the solvent resulting in an array of beads with varying sizes. Patterns with up to 20 passes were experimentally obtained. The beads' height was seen to be independent of the number of passes. The process reported is a simple, fast, and low-cost method for deposition of bead arrays with varying diameters.
A Comparison of Feature Selection Methods for the Detection of Breast Cancers in Mammograms: Adaptive Sequential Floating Search vs. Genetic Algorithm

This paper presents a comparison of feature selection methods for a unified detection of breast cancers in mammograms. A set of features, including curvilinear features, texture features, Gabor features, and multi-resolution features, were extracted from a region of 512times512 pixels containing normal tissue or breast cancer. Adaptive floating search and genetic algorithm were used for the feature selection, and a linear discriminant analysis (LDA) was used for the classification of cancer regions from normal regions. The performance is evaluated using A z the area under ROC curve. On a dataset consisting 296 normal regions and 164 cancer regions (53 masses, 56 spiculated lesions, and 55 calcifications), adaptive floating search achieved Az=0.96 with comparison to Az=0.93 of CHC genetic algorithm and Az=0.90 of simple genetic algorithm
Theory and Methodology Fuzzy optimal flow on imprecise structures

The main aim of this paper is to study the maximum flow problem when the underlying associated structure is not well defined and must be modeled as a fuzzy graph. However, to deal with the problem it is necessary to develop several well known concepts from classical theory, in the fuzzy graph context, such as flow, network, and admissible flow. The above maximum flow problem is formulated and solved by using algorithms previously developed by the authors.
UvA-DARE ( Digital Academic Repository ) Optimization and Sampling for NLP from a Unified Viewpoint

The OS* algorithm is a unified approach to exact optimization and sampling, based on incremental refinements of a functional upper bound, which combines ideas of adaptive rejection sampling and of A* optimization search. We first give a detailed description of OS*. We then explain how it can be applied to several NLP tasks, giving more details on two such applications: (i) decoding and sampling with a high-order HMM, and (ii) decoding and sampling with the intersection of a PCFG and a high-order LM.
Can Budget Institutions Counteract Political Indiscipline?

type="main" xml:lang="en"> The budget is an expression of political rather than economic priorities. We confirm this proposition for a group of new and potential members of the European Union, finding that politics dominates. The contemporary practice of democracy can increase budget deficits through not only ideological preferences, but also more fragmented government coalitions and higher voter participation. Long-term structural forces, triggered by societal divisions and representative electoral rules, have more ambiguous implications but also appear to increase budget pressures, as others have also found. However, our most robust, and hopeful, finding is that budget institutions – mechanisms and rules of the budget process – that create checks and balances have significant value in curbing fiscal pressures even when the politics is representative but undisciplined, and when long-term structural forces are unfavourable. — Stefania Fabrizio and Ashoka Mody
Velocity driven haptic rendering

This paper presents a compact method for improving haptic rendering in virtual environments using Level Of Detail (LOD) with force feedback. We have introduced a velocity driven LOD, a new concept in using LOD in haptics. The aim of this approach differs from using LOD techniques in graphics. Our method simplifies the model according to the speed of the user's fingertip. The users fly quickly through the scene and get a rough overview of it. As they slow down, they obtain more and more details. We have enhanced this basic idea by smooth switching between two successive LODs and by mechanisms leading to a more natural perception of dynamically changing surfaces.
Dynamics and stability of self-organized atomic crystals in optical cavities

This work deals with the theory of atoms coupled to the quantum light eld of an optical resonator and driven by lasers. The studies address a regime where, above a critical value of the laser intensity, the atoms spontaneously form regular spatial structures, stabilized by the mechanical e ects of the light. A systematic description of the dynamics leading to self-organized patterns is provided in the semiclassical limit, whereas the resonator eld is treated as a quantum variable. The equilibrium and out-of-equilibrium properties are determined, the experimental observables are characterised. It is shown that these systems constitute a formidable platform to study criticality in driven-dissipative systems characterized by long-range interactions, which here arise from multiple photon scattering between the atoms. Applications for large atomic samples at ultralow temperatures are discussed in the context of ongoing experiments.
Facial feature extraction by kernel independent component analysis

In this paper, we introduce a new feature representation method for face recognition. The proposed method, referred as kernel ICA, combines the strengths of the kernel and independent component analysis (ICA) approaches. For performing kernel ICA, we employ an algorithm developed by F. R. Bach and M. I. Jordan. This algorithm has proven successful for separating randomly mixed auditory signals, but it has never been applied on bidimensional signals such as images. We compare the performance of kernel ICA with classical algorithms such as PCA and ICA within the context of appearance-based face recognition problem using the FERET and ORL databases. Experimental results show that both kernel ICA and ICA representations are superior to representations based on PCA for recognizing faces across days and changes in expressions.
DETECTION OF VIDEO FORGERY: A REVIEW OF LITERATURE

In the current times the level of video forgery has increased on the internet with the increase in the role of malware that has made it possible for any user to upload, download and share objects online including audio, images, and video. Specifically, Video Editor and Adobe Photoshop are some of the multimedia software and tools that are used to edit or tamper medial files. Added to this, manipulation of video sequence in a way that objects within the frame are inserted or deleted are among the common malicious video forgery operations. In the present study, literature concerning video forgery is reviewed primarily those that use several video forgery detection in the form of passive blind method on three types of forgery namely cloning forgery, source cameral identification and splice forgery. The present study employed a video authentication method that detects and determines both region duplication and frame duplication in terms of video forgery, and locates factors that impact video forgery. In the present study, video processing into sub-blocks and the moments geometric features for every macro-block were extracted. This led to the enhanced accuracy of detection. Moreover, the optimum sorting algorithm led to minimized computational time taking account number of blocks and features numbers into consideration.
LC-MS/MS-based quantification of kynurenine metabolites, tryptophan, monoamines and neopterin in plasma, cerebrospinal fluid and brain.

AIM The kynurenine (KYN) pathway is implicated in diseases such as cancer, psychiatric, neurodegenerative and autoimmune disorders. Measurement of KYN metabolite levels will help elucidating the involvement of the KYN pathway in the disease pathology and inform drug development. METHODOLOGY Samples of plasma, cerebrospinal fluid or brain tissue were spiked with deuterated internal standards, processed and analyzed by LC-MS/MS; analytes were chromatographically separated by gradient elution on a C18 reversed phase analytical column without derivatization. CONCLUSION We established an LC-MS/MS method to measure 11 molecules, namely tryptophan, KYN, 3-OH-KYN, 3-OH-anthranilic acid, quinolinic acid, picolinic acid, kynurenic acid, xanthurenic acid, serotonin, dopamine and neopterin within 5.5 min, with sufficient sensitivity to quantify these molecules in small sample volumes of plasma, cerebrospinal fluid and brain tissue.
The Impact of Agricultural Reforms on Tajikistan's Cotton Production Efficiency

This empirical study examines the impact of agricultural reforms on the cotton sector of Tajikistan. It investigates the level and determinants of technical efficiency for a sample of cotton growing regions in Tajikistan. Using unbalanced panel data of 11-years covering the transition period 1992-2002, 34 cotton-producing regions are analysed with a translog stochastic production frontier, including a model for regional-specific technical inefficiencies. The output elasticities, returns to scale, and indices of convergence are also examined. They reveal that the technical inefficiency effects are found to be highly significant in indicating the ranges and variation in regional outputs. The results show that reforms had a significant positive impact on technical efficiency of cotton production, which, in turn, has a substantial contribution to the process of economic development of Tajikistan.
Mobile Application Testing Matrix and Challenges

The adoption of smart phones and the usages of mobile applications are increasing rapidly. Consequently, within limited time-range, mobile Internet usages have managed to take over the desktop usages particularly since the first smart phone-touched application released by iPhone in 2007. This paper is proposed to provide solution and answer the most demandable questions related to mobile application automated and manual testing limitations. Moreover, Mobile application testing requires agility and physically testing. Agile testing is to detect bugs through automated tools, whereas the compatibility testing is more to ensure that the apps operates on mobile OS (Operation Systems) as well as on the different real devices. Moreover, we have managed to answer automated or manual questions through two mobile application case studies MES (Mobile Exam System) and MLM (Mobile Lab Mate) by creating test scripts for both case studies and our experiment results have been discussed and evaluated on whether to adopt test on real devices or on emulators? In addition to this, we have introduced new mobile application testing matrix for the testers and some enterprises to obtain knowledge from
A hidden Markov model for analyzing ChIP-chip experiments on genome tiling arrays and its application to p53 binding sequences

MOTIVATION Transcription factors (TFs) regulate gene expression by recognizing and binding to specific regulatory regions on the genome, which in higher eukaryotes can occur far away from the regulated genes. Recently, Affymetrix developed the high-density oligonucleotide arrays that tile all the non-repetitive sequences of the human genome at 35 bp resolution. This new array platform allows for the unbiased mapping of in vivo TF binding sequences (TFBSs) using Chromatin ImmunoPrecipitation followed by microarray experiments (ChIP-chip). The massive dataset generated from these experiments pose great challenges for data analysis. RESULTS We developed a fast, scalable and sensitive method to extract TFBSs from ChIP-chip experiments on genome tiling arrays. Our method takes advantage of tiling array data from many experiments to normalize and model the behavior of each individual probe, and identifies TFBSs using a hidden Markov model (HMM). When applied to the data of p53 ChIP-chip experiments from an earlier study, our method discovered many new high confidence p53 targets including all the regions verified by quantitative PCR. Using a de novo motif finding algorithm MDscan, we also recovered the p53 motif from our HMM identified p53 target regions. Furthermore, we found substantial p53 motif enrichment in these regions comparing with both genomic background and the TFBSs identified earlier. Several of the newly identified p53 TFBSs are in the promoter region of known genes or associated with previously characterized p53-responsive genes. SUPPLEMENTARY INFORMATION Available at the following URL http://genome.dfci. harvard.edu/~xsliu/HMMTiling/index.html.
Neural Markers of Responsiveness to the Environment in Human Sleep

Sleep is characterized by a loss of behavioral responsiveness. However, recent research has shown that the sleeping brain is not completely disconnected from its environment. How neural activity constrains the ability to process sensory information while asleep is yet unclear. Here, we instructed human volunteers to classify words with lateralized hand responses while falling asleep. Using an electroencephalographic (EEG) marker of motor preparation, we show how responsiveness is modulated across sleep. These modulations are tracked using classic event-related potential analyses complemented by Lempel-Ziv complexity (LZc), a measure shown to track arousal in sleep and anesthesia. Neural activity related to the semantic content of stimuli was conserved in light non-rapid eye movement (NREM) sleep. However, these processes were suppressed in deep NREM sleep and, importantly, also in REM sleep, despite the recovery of wake-like neural activity in the latter. In NREM sleep, sensory activations were counterbalanced by evoked down states, which, when present, blocked further processing of external information. In addition, responsiveness markers correlated positively with baseline complexity, which could be related to modulation in sleep depth. In REM sleep, however, this relationship was reversed. We therefore propose that, in REM sleep, endogenously generated processes compete with the processing of external input. Sleep can thus be seen as a self-regulated process in which external information can be processed in lighter stages but suppressed in deeper stages. Last, our results suggest drastically different gating mechanisms in NREM and REM sleep. SIGNIFICANCE STATEMENT Previous research has tempered the notion that sleepers are isolated from their environment. Here, we pushed this idea forward and examined, across all sleep stages, the brain's ability to flexibly process sensory information, up to the decision level. We extracted an EEG marker of motor preparation to determine the completion of the sensory processing chain and explored how it is constrained by baseline and evoked neural activity. In NREM sleep, slow waves elicited by stimuli appeared to block response preparation. We also used a novel analytic approach (Lempel-Ziv complexity) and showed that the ability to process external information correlates with neural complexity. A reversal of the correlation between complexity and motor indices in REM sleep suggests drastically different gating mechanisms across sleep stages.
Pathologic analysis of carcinoids Histologic re evaluation of 62 cases

Sixty‐two carcinoids originating from varying sites of primitive gut including bronchus were collected, recut, stained with several special stains including argyrophil and argentaffin reactions, and reevaluated from the practical morphological point of view. Morphologically, these carcinoids were classified into A, B, C, D and mixed types. Such a new classification proved to correlate well with the original sites of these tumors. Further classification due to silver impregnations consisted of argyrophil, argentaffin, and non‐reactive types and indicated a certain correlation with tht sites of tumor development as well. Thus, the foregut‐derived carcinoids were predominant in B type and in argyrophil or non‐reactive types, the midgut‐derived carcinoids in A type and in argentaffin type, and the hindgut‐derived carcinoids in mixed type and in non‐reactive type. The results of the present observation have brought about a certain suggestion as to the pathogenetical difference between carcinoids depending upon the embryonic derivations.
HLA‐G promotes myeloid‐derived suppressor cell accumulation and suppressive activity during human pregnancy through engagement of the receptor ILT4

Establishing and maintaining maternal‐fetal tolerance is essential for a successful pregnancy; failure of immunological adaptation to pregnancy leads to severe complications such as abortion or preterm delivery. Myeloid‐derived suppressor cells (MDSCs) are innate immune cells that suppress T‐cell responses, expand during pregnancy and thus may play a role in tolerance induction. Human leucocyte antigen G (HLA‐G) is a major histocompatibility complex (MHC) I molecule with immune‐modulatory properties, which is expressed during pregnancy. Here, we investigated the impact of HLA‐G on MDSCs accumulation and activation in pregnant women. We demonstrate that granulocytic MDSCs (GR‐MDSCs) express receptors for HLA‐G, namely immunoglobulin‐like transcript (ILT) 2 and 4, and that ILT4‐expression by GR‐MDSCs is regulated during pregnancy. Stimulation with soluble HLA‐G (sHLA‐G) increased suppressive activity of GR‐MDSCs, induced MDSCs from peripheral blood mononuclear cells (PBMCs) and led to phosphorylation of the signal transducer and activator of transcription 3 (STAT3) and induction of indoleamine‐2,3‐dioxygenase (IDO) in myeloid cells. Effects of sHLA‐G on MDSC accumulation were mediated through ILT4. These results suggest an interaction between MDSCs and HLA‐G in humans as a potential mechanism for maintaining maternal‐fetal tolerance. Modulating MDSC function during pregnancy via HLA‐G might provide new opportunities for a therapeutic manipulation of immunological pregnancy complications.
Comparing the performance of electrospun and cast nanocomposite film of polyamide-6 reinforced with multi-wall carbon nanotubes

This study aims at fabrication and characterization of two different structures of electrically conductive polyamide 6/multi-wall carbon nanotube nanocomposite films at different multi-wall carbon nanotube concentrations including electrospun nanofibrous and cast films. Morphology, embedded multi-wall carbon nanotubes into nanofiber, thermal behavior, electrical conductivity and wettability of films were characterized. Scanning electron microscopy images depicted that the nanofiber diameter decreased with increased nanofillers. Enhancement of crystallinity, electrical and tensile properties, and simultaneously achieving a low percolation threshold confirmed good nanotube dispersion by employing a polymeric emulsifier, polyvinylpyrrolidone. The electrospun film crystalline content increased 18.5% and the cast ones increased 46.8% at 7 wt. % multi-wall carbon nanotubes loading. The electrospun and cast membrane electrical conductivity increased by 10 and 12 orders of magnitude. These results demonstrated higher values compared to previously reported data for polyamide 6/multi-wall carbon nanotube nanocomposites. The electrospun film Young’s modulus increased 93% and that of casted one increased 267%, due to the increased crystallinity after adding carbon nanotubes into the films.
Image authentication algorithm with recovery capabilities based on neural networks in the DCT domain

In this study, the authors propose an image authentication algorithm in the DCT domain based on neural networks. The watermark is constructed from the image to be watermarked. It consists of the average value of each 8 × 8 block of the image. Each average value of a block is inserted in another supporting block sufficiently distant from the protected block to prevent simultaneous deterioration of the image and the recovery data during local image tampering. Embedding is performed in the middle frequency coefficients of the DCT transform. In addition, a neural network is trained and used later to recover tampered regions of the image. Experimental results shows that the proposed method is robust to JPEG compression and can also not only localise alterations but also recover them.
Automatic Translation Template Acquisition Based on Bilingual Structure Alignment

Knowledge acquisition is a bottleneck in machine translation and many NLP tasks. A method for automatically acquiring translation templates from bilingual corpora is proposed in this paper. Bilingual sentence pairs are first aligned in syntactic structure by combining a language parsing with a statistical bilingual language model. The alignment results are used to extract translation templates which turn out to be very useful in real machine translation.
The New Era of Hepatitis C Virus Therapy

The hepatitis C virus (HCV) has a significant medical and economic impact on societies around the world, and it has been estimated that 130-180 million people are infected with HCV. Therapies for HCV are currently undergoing a revolution. In recent years, several new treatments have been approved by the United States Food and Drug Administration, and many other treatments are in phase II or III clinical trials, including direct antiviral agents (DAAs). Due to recent major advances in the field of HCV therapy, a summary of findings on new HCV therapies are provided in this review article, including reports on new DAAs.
Computerized tomography of the brain for elderly patients presenting to the emergency department with acute confusion

Objective: Confusion is a common reason for presentation of elderly patients to the ED. There are many potential causes of confusion, which include acute neurological events. Computerized tomography (CT) scans are often routinely ordered to investigate confusion, despite the recommendation of guidelines against routine use. The aim of the present study was to determine the usefulness of CT brain scans in a prospective cohort of confused elderly patients presenting to an ED.