Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigations on organic fluorophore doped silica nanoparticles by apertureless scanning near-field optical microscopy

Colloidal nanoparticles represent an interesting class of materials as they exhibit unique optical, electronic and magnetic properties. Nanoscale optical imaging is essential for observing in detail the optical properties of these materials and for optimizing the associated synthesis procedures in order to make them fit a specific purpose. In the presented experiment we have employed Apertureless Scanning Near-Field Optical Microscopy (ASNOM) for imaging silica nanoparticles that incorporate through covalent bonds an organic fluorophore, 9-aminoacridine. Our results consolidate the current lines of evidence which show that ASNOM imaging has the potential to image both morphological and optical properties of colloidal nanoparticles in very high detail.
OPEN SOURCE AND THE SOFTWARE INDUSTRY HOW FIRMS DO BUSINESS OUT OF AN OPEN INNOVATION PARADIGM

VERY PRELIMINARY VERSION PLEASE DO NOT QUOTE Abstract Open Source Software (OSS) represents an “open innovation” paradigm based on knowledge produced and shared by developers and users. The pa per inquires how OSS challenges the three Teece’s building blocks. New findings from a large survey of European software companies, show that within the OSS paradigm: (i) O SS can be a sustainable business model even in the absence of any appropriability; (ii) complementary assets are distributed collectively and made widely available without the need for dedicated contractual arrangements; (iii) a de facto dominant design may stem from a community of users/producers even independently of the presence of powerful large companies.
Induction of alternative lengthening of telomeres-associated PML bodies by p53/p21 requires HP1 proteins

Alternative lengthening of telomeres (ALT) is a recombination-mediated process that maintains telomeres in telomerase-negative cancer cells. In asynchronously dividing ALT-positive cell populations, a small fraction of the cells have ALT-associated promyelocytic leukemia nuclear bodies (APBs), which contain (TTAGGG)n DNA and telomere-binding proteins. We found that restoring p53 function in ALT cells caused p21 up-regulation, growth arrest/senescence, and a large increase in cells containing APBs. Knockdown of p21 significantly reduced p53-mediated induction of APBs. Moreover, we found that heterochromatin protein 1 (HP1) is present in APBs, and knockdown of HP1α and/or HP1γ prevented p53-mediated APB induction, which suggests that HP1-mediated chromatin compaction is required for APB formation. Therefore, although the presence of APBs in a cell line or tumor is an excellent qualitative marker for ALT, the association of APBs with growth arrest/senescence and with “closed” telomeric chromatin, which is likely to repress recombination, suggests there is no simple correlation between ALT activity level and the number of APBs or APB-positive cells.
The adaptation of cognitive behavioural therapy for adult Maori clients with depression: A pilot study

A semi­structured cognitive behavioural therapy (CBT) programme for depression was adapted for use with Maori adult clients with depression. Adaptations were developed in consultation with an advisory group consisting of Maori clinical psychologists and kaumatua with experience working in mental health services. The programme was piloted with 2 participants who were clients of a Maori mental health service. The programme builds on a more traditional CBT treatment programme by integrating concepts such as whakatauki, whanaungatanga, whanau involvement, and whakapapa into the therapeutic context. Despite limitations the results demonstrate considerable promise. Depressive symptoms increased substantially in both cases and both clients reflected positively on the adaptations incorporated into therapy.
Video Semantic Concept Detection Based on Multi-modality Fusion

Multiple kernel learning methods have a widespread application in visual concept learning and BoVW method has been widely used dues to its excellent categorization performance. However, most canonical multiple kernel learning methods employ a stationary kernel combination format which assigns a uniform kernel weights over the input space. And BoVW method aimed to resolve the problem that the time efficiency of BoVW method decreases as the visual data scales up. As it is true for human perception, learning from multi-modalities has become an effective scheme for various information retrieval problems. In this paper, we propose a novel multi-modality fusion approach for video search, where the search modalities are derived from a diverse set of knowledge sources. Our proposed approach, explores a large set of predefined semantic concepts for computing multi-modality fusion weights by a new method. Experimental results validate the effectiveness of our approach, which outperforms the existing multi-modality fusion methods.
Programmable Frequency Divider for PLL Applications

--Today, the trend is developing whole Systems on a Chip (SoC), that is: integrate all the electronic system’s functions, including digital and analog circuits, on a single silicon die. The Application Specific Integrated Chip (ASIC) is the back end process of the VLSI technology. The ASIC design aims at the designing the customized digital and analog IC for application specific. This paper proposes the design & implementation of a programmable frequency divider (PFD) for PLL applications operating at 100MHz. Here the prescaler architecture is been designed & this architecture is applied to a 5/6 dual modulus prescaler to obtain a particular range of clock frequencies. This PFD has been implemented using 0.18um TSMC CMOS technology with the power consumption of about 0.96mW under 3.3V power supply. Measurement results show that it is very successful in planned frequency division.
Learning to Identify Arabic and German Dialects using Multiple Kernels

We present a machine learning approach for the Arabic Dialect Identification (ADI) and the German Dialect Identification (GDI) Closed Shared Tasks of the DSL 2017 Challenge. The proposed approach combines several kernels using multiple kernel learning. While most of our kernels are based on character p-grams (also known as n-grams) extracted from speech transcripts, we also use a kernel based on i-vectors, a low-dimensional representation of audio recordings, provided only for the Arabic data. In the learning stage, we independently employ Kernel Discriminant Analysis (KDA) and Kernel Ridge Regression (KRR). Our approach is shallow and simple, but the empirical results obtained in the shared tasks prove that it achieves very good results. Indeed, we ranked on the first place in the ADI Shared Task with a weighted F1 score of 76.32% (4.62% above the second place) and on the fifth place in the GDI Shared Task with a weighted F1 score of 63.67% (2.57% below the first place).
Multiband fractal planar inverted F antenna (F-PIFA) for mobile phone application

The design of a novel Fractal planar inverted F antenna (F-PIFA) based on the self affinity property is presented in this paper. The procedure for designing a Fractal Planar Inverted F Antenna is explained and three different iterations are designed for use in cellular phones. The F-PIFA has a total dimension of 27 mm × 27 mm and has been optimized to be operational at GSM (Global System for Mobile Communication), UMTS (Universal Mobile Telecommunication System) and HiperLAN (High Performance Radio LAN) with the frequencies range from 1900 MHz to 2100 MHz, 1885 to 2200 MHz and 4800 MHz to 5800 MHz respectively. The antenna achieved −6 dB return loss at the required GSM, UMTS and HiperLan frequencies with and has almost omnidirectional radiation pattern. This antenna has been tested using realistic mobile phone model and has met the performance criteria for a mobile phone application. Simple semi-empirical formulas of the operational frequency, numerical calculation and computational SAR of the antenna also has been presented and discussed.
Dynamics of software maintenance

As the information technology industry gains maturity, the number of software systems having moved into maintenance is rapidly growing. Often these systems are also potential candidates for outsourcing. However, adequate information regarding size, complexity, reliability, maintainability etc. of these systems is often missing. This makes the task of estimating maintenance efforts for any such system difficult for the organization owning the systems as well as for a software services vendor bidding to outsource maintenance of the system. This is further compounded by human and management factors related to maintenance activities such as management focus, client attitude, engineers' attitude, the need for multi-location support teams etc. These factors make the problem of objectively estimating software maintenance effort almost intractable.We submit that software maintenance is of equal if not more fundamental importance to the software industry, and has not received the attention it deserves, especially in the context of estimation models.This paper describes a holistic approach towards a study of the factors affecting the effort involved in maintenance of existing software systems. It describes how one could build a systems dynamics model to predict the effort involved to maintain a software system, based on qualitative and qualitative inputs.
The participation and influence of teacher unions on education reforms in an independent Namibia

i DECLARATION . iii DEDICATION . iv ACKNOWLEDGEMENTS . v ABBREVIATIONS AND ACRONYMS . vi Table of contents . viii List of tables . x Chapter 1 .
Functional Dissection of the Nascent Polypeptide-Associated Complex in Saccharomyces cerevisiae

Both the yeast nascent polypeptide-associated complex (NAC) and the Hsp40/70-based chaperone system RAC-Ssb are systems tethered to the ribosome to assist cotranslational processes such as folding of nascent polypeptides. While loss of NAC does not cause phenotypic changes in yeast, the simultaneous deletion of genes coding for NAC and the chaperone Ssb (nacΔssbΔ) leads to strongly aggravated defects compared to cells lacking only Ssb, including impaired growth on plates containing L-canavanine or hygromycin B, aggregation of newly synthesized proteins and a reduced translational activity due to ribosome biogenesis defects. In this study, we dissected the functional properties of the individual NAC-subunits (α-NAC, β-NAC and β’-NAC) and of different NAC heterodimers found in yeast (αβ-NAC and αβ’-NAC) by analyzing their capability to complement the pleiotropic phenotype of nacΔssbΔ cells. We show that the abundant heterodimer αβ-NAC but not its paralogue αβ’-NAC is able to suppress all phenotypic defects of nacΔssbΔ cells including global protein aggregation as well as translation and growth deficiencies. This suggests that αβ-NAC and αβ’-NAC are functionally distinct from each other. The function of αβ-NAC strictly depends on its ribosome association and on its high level of expression. Expression of individual β-NAC, β’-NAC or α-NAC subunits as well as αβ’-NAC ameliorated protein aggregation in nacΔssbΔ cells to different extents while only β-NAC was able to restore growth defects suggesting chaperoning activities for β-NAC sufficient to decrease the sensitivity of nacΔssbΔ cells against L-canavanine or hygromycin B. Interestingly, deletion of the ubiquitin-associated (UBA)-domain of the α-NAC subunit strongly enhanced the aggregation preventing activity of αβ-NAC pointing to a negative regulatory role of this domain for the NAC chaperone activity in vivo.
Automatic Transcription of Piano Music

A hidden Markov model approach to piano music transcription is presented. The main difﬁculty in applying traditional HMM techniques is the large number of chord hypotheses that must be considered. We address this problem by using a trained likelihood model to generate reasonable hypotheses for each frame and construct the search graph out of these hypotheses. Results are presented using a recording of a movement from Mozart’s Sonata 18, K. 570.
Protocol for Biomarker Ratio Imaging Microscopy with Specific Application to Ductal Carcinoma In situ of the Breast

This protocol describes the methods and steps involved in performing biomarker ratio imaging microscopy (BRIM) using formalin fixed paraffin-embedded (FFPE) samples of human breast tissue. The technique is based on the acquisition of two fluorescence images of the same microscopic field using two biomarkers and immunohistochemical tools. The biomarkers are selected such that one biomarker correlates with breast cancer aggressiveness while the second biomarker anti-correlates with aggressiveness. When the former image is divided by the latter image, a computed ratio image is formed that reflects the aggressiveness of tumor cells while increasing contrast and eliminating path-length and other artifacts from the image. For example, the aggressiveness of epithelial cells may be assessed by computing ratio images of N-cadherin and E-cadherin images or CD44 and CD24 images, which specifically reflect the mesenchymal or stem cell nature of the constituent cells, respectively. This methodology is illustrated for tissue samples of ductal carcinoma in situ (DCIS) and invasive breast cancer. This tool should be useful in tissue studies of experimental cancer as well as the management of cancer patients.
Dimension reduction for nonelliptically distributed predictors

Sufficient dimension reduction methods often require stringent conditions on the joint distribution of the predictor, or, when such conditions are not satisfied, rely on marginal transformation or reweighting to fulfill them approximately. For example, a typical dimension reduction method would require the predictor to have elliptical or even multivariate normal distribution. In this paper, we reformulate the commonly used dimension reduction methods, via the notion of "central solution space," so as to circumvent the requirements of such strong assumptions, while at the same time preserve the desirable properties of the classical methods, such as √n-consistency and asymptotic normality. Imposing elliptical distributions or even stronger assumptions on predictors is often considered as the necessary tradeoff for overcoming the "curse of dimensionality," but the development of this paper shows that this need not be the case. The new methods will be compared with existing methods by simulation and applied to a data set.
Adaptive filtering exploiting band-limited property of sound field in the wave domain

Massive multichannel sound reproduction is necessary for highly immersive full-duplex communication. Efficient echo cancellation between massive loudspeakers and microphones is indispensable, and wave-domain adaptive filtering reduces the computational complexity drastically. We propose to further reduce this complexity by exploiting the band-limited property that the sound field has in the space-time-frequency representation. Experimental evaluations support the applicability of the proposed method.
Integrative Analysis of Microarray Data to Reveal Regulation Patterns in the Pathogenesis of Hepatocellular Carcinoma

Background/Aims The integration of multiple profiling data and the construction of a transcriptional regulatory network may provide additional insights into the molecular mechanisms of hepatocellular carcinoma (HCC). The present study was conducted to investigate the deregulation of genes and the transcriptional regulatory network in HCC. Methods An integrated analysis of HCC gene expression datasets was performed in Gene Expression Omnibus. Functional annotation of the differentially expression genes (DEGs) was conducted. Furthermore, transcription factors (TFs) were identified, and a global transcriptional regulatory network was constructed. Results An integrated analysis of eight eligible gene expression profiles of HCC led to 1,835 DEGs. Consistent with the fact that the cell cycle is closely related to various tumors, the functional annotation revealed that genes involved in the cell cycle were significantly enriched. A transcriptional regulatory network was constructed using the 62 TFs, which consisted of 872 TF-target interactions between 56 TFs and 672 DEGs in the context of HCC. The top 10 TFs covering the most downstream DEGs were ZNF354C, NFATC2, ARID3A, BRCA1, ZNF263, FOXD1, GATA3, FOXO3, FOXL1, and NR4A2. This network will appeal to future investigators focusing on the development of HCC. Conclusions The transcriptional regulatory network can provide additional information that is valuable in understanding the underlying molecular mechanism in hepatic tumorigenesis.
Rule Refinement Using the Probabilistic Rule Generator

This work treats the case of expert-originated hypotheses which are to be modified or refined by training event data. The method accepts the hypotheses in the form of weighted VL1 expressions and uses the probabilistic rule generator, PRG. The theory of operation, verified by experimental results, provides for any degree of hypothesis modification, ranging from minor perturbation to complete replacement according to supplied confidence weightings.
Involvement of RhoA/Rho kinase signaling in dehydroepiandrosterone's protection against monocrotaline-induced pulmonary hypertension in pneumonectomized rats

ABSTRACT RhoA/Rho kinase (ROCK) signaling plays a key role in the pathogenesis of experimental pulmonary hypertension (PH). Dehydroepiandrosterone (DHEA), a naturally occurring steroid hormone, effectively inhibits chronic hypoxic PH, but the responsible mechanisms are unclear. This study tested if DHEA was also effective in treating monocrotaline (MCT)-induced PH in left pneumonectomized rats, and if inhibition of RhoA/ROCK signaling was involved in DHEA’s protective effect. Three weeks after MCT injection, pneumonectomized rats developed PH with severe vascular remodeling, including occlusive neointimal lesions in pulmonary arterioles. In lungs from these animals, we detected cleaved (constitutively active) ROCK I, as well as increases in activities of RhoA and ROCK, and in ROCK II protein expression. Chronic DHEA treatment (1%, by food for 3 wks) markedly inhibited the MCT-induced PH (mean pulmonary artery pressures after treatment with 0 and 1% DHEA were 33 ± 5 and 16 ± 1 mmHg, respectively) and severe pulmonary vascular remodeling in pneumonectomized rats. The MCT-induced changes in RhoA/ROCK-related protein expression were nearly normalized by DHEA. A 3-week DHEA treatment (1%) started 3 weeks after MCT injection completely inhibited the progression of PH (mean pulmonary artery pressures after treatment with 0 and 1% DHEA were 47 ± 3 and 30 ± 3 mmHg, respectively), and this treatment also resulted in 100% survival in contrast to 30% in DHEA-untreated rats. These results suggest that inhibition of RhoA/ROCK signaling, including the cleavage and constitutive activation of ROCK I, is an important component of DHEA’s impressive protection against MCT-induced PH in pneumonectomized rats.
Computation of Localized Flow for Steady and Unsteady Vector Fields and Its Applications

This paper provides key insights into the construction and evaluation of interpersonal simulators - systems that enable interpersonal interaction with virtual humans. Using an interpersonal simulator, two studies were conducted that compare interactions with a virtual human to interactions with a similar real human. The specific interpersonal scenario employed was that of a medical interview. Medical students interacted with either a virtual human simulating appendicitis or a real human pretending to have the same symptoms. In study I (n=24), medical students elicited the same information from the virtual and real human, indicating that the content of the virtual and real interactions were similar. However, participants appeared less engaged and insincere with the virtual human. These behavioral differences likely stemmed from the virtual human's limited expressive behavior. Study II (n=58) explored participant behavior using new measures. Nonverbal behavior appeared to communicate lower interest and a poorer attitude toward the virtual human. Some subjective measures of participant behavior yielded contradictory results, highlighting the need for objective, physically-based measures in future studies
Loss of CADM1/TSLC1 Expression Is Associated with Poor Clinical Outcome in Patients with Esophageal Squamous Cell Carcinoma

Aims. We sought to determine the relationship between CADM1/TSLC1 expression and clinicopathological characteristics in patients with esophageal squamous cell carcinoma (ESCC) and the correlation with survival. Materials and Methods. Two hundred and ninety-three ESCC tissues and paired adjacent normal esophageal tissues were immunohistochemically assessed in this study. The association of CADM1/TSLC1 with clinicopathological parameters, as well as disease-free survival (DFS) and overall survival (OS), was determined based on the Kaplan-Meier method and Cox regression models. Results. CADM1/TSLC1 was detected in 236 (80.5%) tumor tissues and 19 (8.0%) paired adjacent normal esophageal tissues. Decreased CADM1/TSLC1 expression was correlated with more advanced histological grade. CADM1/TSLC1 negative tumors were more frequently observed in male cases than in female cases. DFS and OS in the CADM1/TSLC1 negative group were significantly shorter than those in the positive group, particularly in male patients with ESCC. Conclusion. Loss or reduction of CADM1/TSLC1 expression is associated with more advanced histological grade and predicts early recurrence and short survival duration. Thus, loss of CADM1/TSLC1 could be a prognostic factor that can be used to assess the risk of recurrence and survival.
3D pooling on local space-time features for human action recognition

Successful approaches use local space-time features for human action recognition task including hand designed features or learned features. However these methods need a wise technique to encode local features to make a global representation for video. For this, some methods use K-means vector quantization to histogram each video as a bag of word. Pooling is a way used for global representation of an image. This method pools the local image feature over some image neighborhood. In this paper we extend pooling method called 3D pooling for global representation of video. 3D pooling represents each video by concatenating pooled feature vectors achieved from 8 equal regions of video. We also applied stacked convolutional ISA as local feature extractor. We evaluated our method on KTH data set and got our best result using max pooling. It improves the performance of highly demanded earlier methods.