Miracle-dz/UniFAR-FTUs huggingface dataset:
Beta Testing of a Mobile Application: A Case Study

Beta testing is the last stage of testing, and normally involves sending the product for beta testing and real-world exposure outside the company. Beta testing is often preceded by a round of testing called alpha testing. Beta testing can be considered a form of external user acceptance testing. Software in the beta phase will generally have many more bugs in it than completed applications, as well as speed and performance issues that may still cause crashes or data loss. Beta testing is the first opportunity to get real feedback from target customers. The launch of a mobile application is especially crucial because it is the single biggest opportunity to get an application discovered in the mobile markets. In this article, the beta testing of mobile applications is presented. Our aim is to identify the optimal number of testers, who can reveal the majority of errors and mistakes during beta testing. The findings were obtained through the case study research method.
Process variability in FinFET standard cells with different transistor sizing techniques

This work evaluates the impact of process variations on the electrical behavior of a set of combinational cells considering different transistor sizing techniques: minimum sizing, logical effort and delay-optimized sizing. The optimization is done by a transistor sizing tool that employs geometric programming. The main point is to observe how transistor sizing techniques could be explored for the FinFET standard cells design. Results show that cells sized accordingly logical effort technique are more sensible to process variability when compared with minimum transistor sizing. The best process variability robustness is achieved by adopting the delay-optimized sizing technique.
Obestatin/Ghrelin Ratio as a New Activity Index in Ulcerative Colitis

Background and Aim: Ulcerative colitis (UC) is an immune-mediated systemic inflammatory process that destroys the intestinal mucosa. Ghrelin, an appetite-regulatory hormone, has anti-inflammatory effects including a decrease in circulating cytokines. Some reports demonstrated a strong relationship between the serum ghrelin level and the severity of mucosal inflammation in the gastrointestinal tract. The aim is to investigate serum levels and colonic mucosal mRNA expression of ghrelin, obestatin, and obestatin/ghrelin ratio in patients with UC and to determine their potential as markers for UC disease activity. Patients and Methods: seventy-five outpatients with UC and 45 age- and sex-matched healthy volunteers were enrolled in this study after written conscious consent and approval by the Institutional Review Board of Mansoura University. UC was diagnosed by conventional clinical, radiological, endoscopic, and histopathological criteria. Serum ghrelin, obestatin levels, and their mucosal mRNA expression were measured by ELISA kits and a real-time quantitative reverse transcriptase polymerase chain reaction according to the manufacturer’s protocols. Results: Serum levels and mucosal mRNA expression of ghrelin were significantly higher in patients with active UC than patients in remission p˂0.0001). Obestatin/ghrelin ratio was significantly lower in patients with active UC (0.26±0.08) than those in remission (0.523±0.16; p˂0.0001). Obestatin/ghrelin ratio was negatively and significantly correlated with inflammation and endoscopic scores, colitis activity index, serum ghrelin level, and its mucosal mRNA expression (p˂0.05). Conclusion: obestatin/ghrelin ratio might be a reliable surrogate non-invasive marker of disease activity in UC with significantly high sensitivity, specificity, predictive values, and diagnostic accuracy.
Mapping and characterization of Induced Polarization in airborne TEM data from central East Greenland : application of a Self-Organizing Map procedure

nduced Polarization (IP) effects were observed in airborne Time Domain EM (TEM) data acquired in central East Greenland in the context of exploration for disseminated sulphides in a sedimentary basin. Some of the IP anomalies were targeted by drilling which revealed the absence of mineralization. In order to understand the possible causes of the IP effects we first identified them in the TEM data. IP indicators were extracted from the shape of the transient curves at every measurement location and were analysed by using a Self-Organizing Map (SOM) procedure. Results from K-mean clustering of the SOM are visualized on a geographical map showing the transient curves’ characteristics. Some of the clusters are clearly correlated with the geology whereas others merely reflect recordings below the noise level. In order to interpret the cause of the IP anomalies the airborne TEM data were inverted for the Cole-Cole parameters.
Autonomous dual-mode (PAM2/4) serial link transceiver with adaptive equalization and data recovery

This paper describes an adaptively equalized, dual-mode (PAM2 one-tap DFE/PAM4) 0.13 /spl mu/m CMOS transceiver chip, and the techniques used to continuously adapt the link. Interestingly, with only minor modification the same hardware needed to implement a PAM4 system can be used to implement a PAM2 loop-unrolled single-tap decision-feedback equalization (DFE) receiver. Adaptive equalization using data-based update filtering allows continuous updates while minimizing the required sampler front-end hardware and significantly reduces the cost of implementation in multi-level signaling schemes. To allow the transmitter to adapt to the channel, the link uses common-mode signaling to create a back-channel communication path over the existing pair of wires. The design uses a three-level return-to-null signaling scheme which allows the receiver to simultaneously extract voltage and timing references and minimize the required receiver hardware. The measured results indicate that this back-channel achieves reliable communication without noticeable impact on the forward link for back-channel data rates of up to 16 Mb/s and swings of 20-100 mV.
Systematic review of patients' participation in and experiences of technology-based monitoring of mental health symptoms in the community

Objectives To review systematically the literature on patients’ experiences of, and participation in, technology-based monitoring of mental health symptoms. This practice was defined as patients monitoring their mental health symptoms, emotions or behaviours outside of routine clinical appointments by submitting symptom data using technology, with feedback arising from the data (for example, supportive messages or symptom summaries, being sent to the patient, clinician or carer). Design Systematic review following PRISMA guidelines of studies evaluating technology-based symptom monitoring. Tools from narrative synthesis were used to analyse quantitative findings on participation rates and qualitative findings on patient views. Data sources PubMed, EMBASE, PsycINFO, BNI, CINAHL, Cochrane Registers and Web of Science electronic databases were searched using a combination of ‘psychiatry’, ‘symptom monitoring’ and ‘technology’ descriptors. A secondary hand search was performed in grey literature and references. Results 57 papers representing 42 studies met the inclusion criteria for the review. Technology-based symptom monitoring was used for a range of mental health conditions, either independently of a specific therapeutic intervention or as an integrated component of therapeutic interventions. The majority of studies reported moderate-to-strong rates of participation, though a third reported lower rates. Qualitative feedback suggests that acceptability of monitoring is related to perceived validity, ease of practice, convenient technology, appropriate frequency and helpfulness of feedback, as well as the impact of monitoring on participants’ ability to manage health and personal relationships. Conclusions Such symptom monitoring practices appear to be well accepted and may be a feasible complement to clinical practice. However, there is limited availability of data and heterogeneity of studies. Future research should examine robustly patients’ role in the development and evaluation of technology-based symptom monitoring in order to maximise its clinical utility.
Human Activity Encoding and Recognition Using Low-level Visual Features

Automatic recognition of human activities is among the key capabilities of many intelligent systems with vision/perception. Most existing approaches to this problem require sophisticated feature extraction before classification can be performed. This paper presents a novel approach for human action recognition using only simple low-level visual features: motion captured from direct frame differencing. A codebook of key poses is first created from the training data through unsupervised clustering. Videos of actions are then coded as sequences of super-frames, defined as the key poses augmented with discriminative attributes. A weighted-sequence distance is proposed for comparing two super-frame sequences, which is further wrapped as a kernel embedded in a SVM classifier for the final classification. Compared with conventional methods, our approach provides a flexible non-parametric sequential structure with a corresponding distance measure for human action representation and classification without requiring complex feature extraction. The effectiveness of our approach is demonstrated with the widely-used KTH human activity dataset, for which the proposed method outperforms the existing state-of-the-art.
Faulty resistance sectioning technique for resistive bridging fault ATPG systems

This paper proposes a bridging fault resistance sectioning technique for high speed generation systems of test sets which detect all the resistive bridging faults detectable by logic testing, targeting all the resistive bridging faults each of which ranges from zero ohm to infinity resistance. The previously proposed ATPG systems for this problem dealt with each bridging fault as a target fault for test generation, and consequently the systems must have handled "set operations on the number space", which made the test generation algorithm very complicated and the fault simulation time-consuming. To solve these problems, our method partitions each bridging fault which ranges from zero ohm to infinity resistance into mutually exclusive subsections by a partitioning procedure, and deals with each subsection as a target fault in ATPG. This faulty resistance sectioning technique allows us to exclude the "set operations on the number space" from ATPG procedures, and leads to a simple and high speed ATPG system.
Auditory Representation Learning

Representation of a speech and audio signal based on human auditory processing is of significant interest in developing features for speech and audio processing applications [1]. The traditional approaches to extract the auditory features are either based on computational or mathematical models of auditory system [2–5]. Recently, representation learning (RL) has gained a significant interest for feature learning in various signal processing areas including speech processing [6]. In the speech processing literature, it is also called Automatic Speech Analysis (ASA) that involves the extraction of meaningful information using computers from the speech signals [7]. There are various approaches proposed for auditory modeling using RL techniques [8–18]. Unsupervised learning is one of the important forms of representation learning since many human learning tasks are unsupervised [19], [20]. A motivation for this thesis is the first notable study conducted by M. Lewicki to show that the human auditory system (HAS) is adapted to the sound statistics [8]. The experimental results in [8] showed that the optimal auditory codes are different according to the statistics of sounds. The objective of this thesis is to propose a novel auditory representation learning model that can be used in speech and audio processing applications. In this thesis, we have developed unsupervised auditory filterbank learning using a Convolutional Restricted Boltzmann Machine (ConvRBM). Our proposed ConvRBM model has been successfully applied in automatic speech recognition (ASR) [21–25], Environmental Sound Classification (ESC) [26], spoof speech detection (SSD) [27], [28], and infant cry classification (ICC) [29], [30]. Next, we discuss the key research challenges in the development of auditory models.
Magnetic resonance elastography: a method for the noninvasive and spatially resolved observation of phase transitions in gels.

Dynamic magnetic resonance elastography (MRE) is a new imaging technique 1 recently developed for the noninvasive determination of biomechanical properties of biological tissue. 2 Compared to traditional medical palpation techniques, MRE is characterized by a high spatial resolution and a high sensitivity to the varying stiffness between healthy and pathologic tissues even in nonaccessible body regions. 3 Moreover, MRE also provides new information for other research fields. We report the spatially and temporally resolved observation of the sol/gel phase transition in a thermo-reversible gel. Observed wave patterns were reproduced using a model calculation based on temperature-dependent biomechanical properties of the sample. Dynamic MRE is based on the visualization of propagating shear waves in harmonically excited samples. The shear waves are usually generated mechanically with excitation frequencies between 50 and 600 Hz. 1 Minimum amplitudes for particle displacement are in the order of 0.1 Im. This enables the transmission of shear waves with low damping into the sample. The wave patterns, which depend on the local biomechanical properties of the sample, are visualized by using motion-sensitive MRI techniques. 1 Maps of local shear stiffness or shear moduli (elastograms) can be reconstructed from the wave images. 4 The gel phantom was prepared by dissolving 22.5 g of agar (1.5%) in 1.5 L of water heated to 90 °C. The fluid gel was examined in a double-walled container open at the top. The cooling of the sample (total cooling time 5 h), monitored with a thermometer between 60 and 25 °C, showed an exponential time dependence. Shear waves with a frequency of 200 Hz were induced parallel to the B0-field direction (z) by a copper coil fixed to a pivoting carbon fiber rod connected with the surface of the gel. The excitation device was fixed to the standard head coil of a clinical scanner (1.5 T, Siemens, Erlangen, Germany). Data were
In Vivo Study of Gold-Nanoparticles Using Different Extracts for kidney, liver function and Photocatalytic Application

We report novel gold nanoparticles by green method for different fruit extracts have gaining greater attention due to its versatile properties in different applications. In this article, GNPs synthesis is demonstrated successfully using fresh fruit extract of punica granatum and fragaria. The optical properties, morphology and elemental analysis of samples was done by using) different characterization techniques like SEM EDX and UV-Visible spectroscopy Biocompatibility of GNPs was determined by ALT, AST, ALP, Urea, Creatinine tests and also to investigate the effects of prepared GNPs on the kidney and liver functions. The GNPs prepared by fruit extract of punica granatum have more effects on the rabbits than GNPs prepared from fragaria but this effect normalizes after three days which shows its biocompatibility. To explore the photocatalytic activity of the GNPs the photocatalytic degradation of MB dye is also investigated. The results revealed that GNPs prepared through green synthesis route are found to be efficient enhancement in the degradation of MB dye in visible region due to large surface area. These particles were more active in catalytic reduction due to their high surface energy and in bio-medical applications as biocompatibility.
IL10 and IL10 Receptor Gene Variation and Outcomes After Unrelated and Related Hematopoietic Cell Transplantation

Background. Results of a previous study with human leukocyte antigen (HLA)-identical siblings showed individual and synergistic associations of single nucleotide polymorphisms in the promoter region of the recipient’s IL10 gene and the donor’s IL10 receptor &bgr; (IL-10RB) gene with development of grades III–IV acute graft-versus-host disease (GVHD) after allogeneic hematopoietic cell transplantation. Methods. In this study of 936 patients who had unrelated donors, genotypes of single nucleotide polymorphisms in the IL10 gene and the IL-10RB gene were evaluated as correlates with outcomes after transplantation. Results. We found no statistically significant associations of polymorphisms at positions −3575, −2763, −1082, and −592 of the IL10 gene or codon 238 of the IL10RB gene with severe acute GVHD, extensive chronic GVHD or nonrelapse mortality after hematopoietic cell transplantation. Among HLA-matched unrelated pairs, the patient’s IL10/−592 genotype and donor’s IL10RB/c238 genotype showed trends suggesting individual and combined associations with grades III–IV acute GVHD similar to those observed among patients with HLA-identical sibling donors. Conclusions. Although genetic variation in IL10 pathway affects risk of acute GVHD and non-relapse mortality in HLA-identical sibling transplants, the current results indicate that genetic variation in the IL10 pathway does not significant affect these outcomes in unrelated donor transplants suggesting that the strength of the alloimmune response in the latter exceeds the anti-inflammatory activity of IL10.
A tutorial on simulation conceptual modeling

Conceptual modeling is the abstraction of a simulation model from the part of the real world it is representing; in other words, choosing what to model, and what not to model. This is generally agreed to be the most difficult, least understood, but probably the most important activity to be carried out in a simulation study. In this tutorial we explore the definition, requirements and approach to conceptual modeling. First we ask ‘where is the model? ’ We go on to define the term ‘conceptual model’, to identify the artefacts of conceptual modeling, and to discuss the purpose and benefits of a conceptual model. In so doing we identify the role of conceptual modeling in the simulation project life-cycle. The discussion then focuses on the requirements of a conceptual model, the approaches for documenting a conceptual model, and frameworks for guiding the conceptual modeling activity. One specific framework is described and illustrated in more detail. The tutorial concludes with a discussion on the level of abstraction.
Development and optimization of a sublingual tablet formulation for physostigmine salicylate

Development and optimization of a sublingual tablet formulation for physostigmine salicylate This study is aimed to design and optimize a sublingual tablet formulation of physostigmine salicylate, an effective drug in Alzheimer's disease and nerve gas poisoning, by means of the D-optimal experimental design methodology. Polyvinyl pyrrolidone, lactose, starch 1500 and sodium starch glycolate were used in the formulations as independent variables. Tablets were prepared by the direct compression method and evaluated for their physical properties (tablet hardness, disintegration time and friability), which were regarded as responses in a D-optimal design. Due to the significance of the special cubic model for data fitted, compared to other models, it was used to examine the obtained results. Response surface plots were plotted to study the tablet properties and the optimized overlay plot was generated based on the results and targets considered for the responses. After verification of the optimum checkpoint formulations, an optimized formulation was chosen due to its desirable physical properties and closely observed and predicted values. Drug assay, content uniformity of the dosage unit, drug dissolution and accelerated stability studies were done on the optimum formulation as further experiments. All the obtained results complied with the requirements of a sublingual tablet formulation. Razvoj i optimizacija sublingvalnih tableta fizostigmin salicilata Cilj rada bio je dizajnirati i optimirati sublingvalne tablete fizostigmin salicilata, lijeka učinkovitog u terapiji Alzheimerove bolesti i intoksikacije nervnim plinovitim otrovima, koristeći metodologiju D-optimalnog eksperimentalnog dizajniranja. U formulacijama su kao nezavisne varijable korišteni polivinil pirolidon, laktoza, škrob 1500 i natrijev škrobni glikolat. Tablete su pripravljene metodom izravne kompresije. Njihova fizikalna svojstva (tvrdoća, vrijeme dezintegracije i lomljivost) evaluirana su kao zavisna varijabla u Doptimalnom dizajniranju. Rezultati su najbolje slijedili specijalni kubični model, pa je taj model upotrijebljen za ispitivanje rezultata. Nacrtane su krivulje ovisnosti za proučavanje svojstava tableta. Na temelju njih izrađen je i optimirani prekrivni prikaz prema rezultatima i postavljenim ciljevima za odgovor na lijek. Poslije provjere najboljih kontrolnih formulacija, izabrana je jedna optimirana formulacija temeljem svojih poželjnih fizičkih značajki te uočenih i predviđenih vrijednosti. Ispitivanje lijeka, jednolikosti sadržaja, oslobađanja lijeka i pokusi ubrzanog starenja provedeni su na optimiranoj formulaciji. Dobiveni rezultati odgovaraju zahtjevima za tablete za sublingvalnu primjenu.
Testing the Stability of Implied Probability Density Functions

Implied probability density functions (PDFs) estimated from cross-sections of observed option prices are gaining increasing attention amongst academics and practitioners. To date, however, little attention has been paid to the robustness of these estimates or to the confidence that users can place in the summary statistics (for example the skewness or the 99th percentile) derived from fitted PDFs. This paper begins to address these questions by examining the absolute and relative robustness of two of the most common methods for estimating implied PDFs - the double-lognormal approximating function and the smoothed implied volatility smile methods. The changes resulting from randomly perturbing quoted prices by no more than a half tick provide a lower bound on the confidence intervals of the summary statistics derived from the estimated PDFs. Tests are conducted using options contracts tied to short sterling futures and the FTSE 100 index - both trading on the London International Financial Futures and Options Exchange. The tests show that the smoothed implied volatility smile method dominates the double-lognormal as a technique for estimating implied PDFs when average goodness-of-fits for both methods are comparable.
Visual analysis of attention-based end-to-end speech
 recognition

An end-to-end speech recognition model consisting of a single integrated neural network model was recently proposed. The end-to-end model does not need several training steps, and its structure is easy to understand. However, it is difficult to understand how the model recognizes speech internally. In this paper, we visualized and analyzed the attention-based end-to-end model to elucidate its internal mechanisms. We compared the acoustic model of the BLSTM-HMM hybrid model with the encoder of the end-to-end model, and visualized them using t-SNE to examine the difference between neural network layers. As a result, we were able to delineate the difference between the acoustic model and the end-to-end model encoder. Additionally, we analyzed the decoder of the end-to-end model from a language model perspective. Finally, we found that improving end-to-end model decoder is necessary to yield higher performance.