Miracle-dz/UniFAR-FTUs huggingface dataset:
Flow Cytometric Immunobead Assay for Detection of BCR-ABL1 Fusion Proteins in Chronic Myleoid Leukemia: Comparison with FISH and PCR Techniques

Chronic Myeloid Leukemia (CML) is characterized by a balanced translocation juxtaposing the Abelson (ABL) and breakpoint cluster region (BCR) genes. The resulting BCR-ABL1 oncogene leads to increased proliferation and survival of leukemic cells. Successful treatment of CML has been accompanied by steady improvements in our capacity to accurately and sensitively monitor therapy response. Currently, measurement of BCR-ABL1 mRNA transcript levels by real-time quantitative PCR (RQ-PCR) defines critical response endpoints. An antibody-based technique for BCR-ABL1 protein recognition could be an attractive alternative to RQ-PCR. To date, there have been no studies evaluating whether flow-cytometry based assays could be of clinical utility in evaluating residual disease in CML patients. Here we describe a flow-cytometry assay that detects the presence of BCR-ABL1 fusion proteins in CML lysates to determine the applicability, reliability, and specificity of this method for both diagnosis and monitoring of CML patients for initial response to therapy. We show that: i) CML can be properly diagnosed at onset, (ii) follow-up assessments show detectable fusion protein (i.e. relative mean fluorescent intensity, rMFI%>1) when BCR-ABL1IS transcripts are between 1–10%, and (iii) rMFI% levels predict CCyR as defined by FISH analysis. Overall, the FCBA assay is a rapid technique, fully translatable to the routine management of CML patients.
Overcoming accuracy-diversity tradeoff in recommender systems: A variance-based approach

Abstract. Collaborative filtering and, more generally, recommender systems represent an increasingly popular and important set of personalization technologies that help people navigate through the vast amounts of information. The performance of recommender systems can be evaluated along several dimensions, such as the accuracy of recommendations for each user and the diversity of recommendations across different users. Intuitively, there is a tradeoff between accuracy and diversity, because high accuracy may often be obtained by safely recommending to users the most popular (“bestselling”) items, which can lead to the reduction in recommendation diversity, i.e., less personalized recommendations. And conversely, higher diversity can be achieved by trying to uncover and recommend highly idiosyncratic/personalized items for each user, which are inherently more difficult to predict and, thus, may lead to a decrease in recommendation accuracy. In our research we explore different ways to overcome this accuracy-diversity tradeoff, and in this paper we discuss a variance-based approach that can improve both the accuracy and diversity of recommendations obtained from a traditional collaborative filtering technique. We provide empirical results based on several real-world movie rating datasets.
Emotionality and Composition in Thai and in English

This empirical study examined the perceptions and experiences of nine Thai college student writers' expression of emotions in poetry, narrative, and opinionated writing written in their first (L1) and second (L2) languages: Thai and English. The study focused on the participants' perspectives in order to gain more understanding of the phenomenon of expressing emotions in writing in different languages. The participants were nine Thai college students who attended a public university in Thailand. The data, gathered over three months, included 54 written responses and 36 interview sessions. The written responses included poems, narrative stories, and opinionated writing both in Thai and English. The interviews were conducted in Thai, transcribed, and translated into English. The interviews were then analyzed from two aspects: focusing on each individual's perceptions and experiences and focusing on genre writing and their emotionality writing experiences. This study's analysis suggested that the participants had positive responses to the written tasks when expressing emotions through different genres in L1 and L2. It also showed that emotions are one of the crucial elements in participants' writing experiences and that cultural and linguistic identities played important roles in the tasks of emotionality writing in both languages. The emotionality writing helped L2 learners gain meta-linguistic awareness of L1 and L2 and reflect on their language learning and personally significant experiences. Through that awareness, L2 learners could become educators for others who want to learn about their L1. The emotionality written tasks allowed the participants to reflect on their language learning and personally significant experiences. This study argued that emotionality writing should be encouraged in L2 writing classrooms and addressed the ramifications of expanding of L2 writing on a pedagogical level.
Spectral analysis of DNA sequence using recursive weiner khinchine theorem: a comparative approach

Locating protein coding regions (exons) in Eukaryotes is one of the key problems of gene identification. The period-3 peaks observed in spectra of exons are often used as the landmark indicating existence of coding region in genes. Spectral Analysis by Discrete Fourier Transform (DFT) and filtering are popular methods adopted by various researchers from the field of Digital Signal Processing to accomplish this purpose. Many of the researchers have used Celegan gene as their sample database for exon prediction. Hence authors in this paper have identified F56F11.4a gene of Celegan Chromosome IE as their test database and have applied Recursive Weiner Khinchine Theorem (RWKT) for spectral analysis. On comparison it shows that results obtained by RWKT method gives better spectral resolution and clarity than DFT method.
Coping with the Sudden Loss of an Indispensable Employee

Using real-time longitudinal survey and interview data, the authors assessed explicit and tacit knowledge flows within a small manufacturing firm for an indispensable employee (IE). They then compared those flows to the flows for a replacement employee (RE) who took over after the IE became ill. As expected, they found that (a) explicit and tacit knowledge outflows to coworkers were greater for the IE than for the RE, and (b) tacit knowledge inflows from coworkers were slightly greater for the RE than for the IE. Explicit knowledge inflows from coworkers were not consistently greater for the RE than for the IE. Surprisingly, the loss of the IE did not have a negative impact on the firm's productivity.
Text World Theory and stories of self: A cognitive discursive approach to identity

This thesis offers a text-worlds-approach to the study of linguistic identity in discursive interaction. It focuses on how settled Chinese migrants in Sheffield, who migrated predominantly from Hong Kong and the New Territories, construct their identities linguistically. To this extent, linguistic interview data is analysed with the use of the conceptual framework Text World Theory (e.g. Gavins 2007a; Werth 1999). As such, this thesis has three central aims: to extend the use of Text World Theory by applying it to spoken discourse; to examine the ways in which people linguistically represent themselves and talk about their life experiences; and to provide insight into the narratives of Chinese migrants and their families in Sheffield in particular. The linguistic data used in this thesis has been collected through 18 months of ethnographic fieldwork at a Chinese complementary school in Sheffield, UK. Based on the outcome of the analytical investigations of linguistic interview data, I aim to offer several original contributions. Firstly, I hope to provide a better understanding of migrant lives, by investigating the narrated experiences of Chinese migrants and their families. Secondly, I offer Text World Theory as a suitable framework for the study of linguistic identity. I extend the framework to the relatively unexplored domain of spoken discourse, synthesising a discursive approach to identity (e.g. Bucholtz and Hall 2005) with a Text World Theory approach (e.g. Gavins 2007a; Werth 1999). I demonstrate that Text World Theory can explain the complex and multi-layered nature of identity through the scope it provides for tracing linguistic self-representation across multiple worlds. Finally, I show that the framework is particularly adept at synthesising macro-level analysis of discursive interaction with detailed micro-level analysis of linguistic choices and their conceptual consequences.
Understanding Population and Individual Risk Assessment: The Case of Polychlorinated Biphenyls

Decisions about how to improve or protect the public health can be, and sometimes necessarily are, made on imprecise science. The regulation of potential human carcinogens in the environment entails a population-risk assessment process intended to reduce risks to less than one additional cancer in 100,000 or 1,000,000 persons. These risk assessment processes, however, may be miscommunicated or misinterpreted in the context of individual cancer risks by scientists, regulators, the lay media, and the public. This commentary will review methods for establishing a causal relationship between carcinogen exposures and cancer risk. It will use the case of polychlorinated biphenyls (PCB) as an example of how to place scientific data into the context of human exposure and cancer risk. PCBs are widespread environmental contaminants and most people have detectable levels of PCBs in their bodies. The primary source for exposure in the general population is through the diet. PCBs are carcinogens in experimental animal models, but how this information can be extrapolated to human risk remains uncertain. PCB experimental studies provide data that are used to regulate and control human exposure, although the epidemiologic evidence fails to establish PCBs as human carcinogens. Thus, what is used for population-risk assessment may not be appropriate for individual-risk assessment or concluding that a causal relationship exists between PCB exposure and cancer risk. The hazards from a carcinogen designated by regulatory and review agencies as a “probable” human carcinogen is often misunderstood out of context about the magnitude of the risk and in what settings. How scientists communicate their results in scientific articles can strongly influence how others interpret their data. Misunderstandings from both the use of regulatory and review-agency opinions and the conclusions espoused by scientists occur in the media, among private physicians counseling their patients about cancer risk, and in the legal settings where plaintiffs seek compensation for exposure and alleged harm (or future harm). This can lead to false conclusions about what caused a cancer in a specific patient, undue anxiety about future cancer risk, inappropriate cancer screening, and attendant increased morbidity due to increased uses of the medical system and complication rates from medical procedures. The communication of research findings by scientists must be presented with caution, resisting the temptation to extrapolate, inappropriately, research data to the general population. (Cancer Epidemiol Biomarkers Prev 2006;15(5):830–9)
An automatic singing transcription system with multilingual singing lyric recognizer and robust melody tracker

A singing transcription system which transcribes human singing voice to musical notes is described in this paper. The fact that human singing rarely follows standard musical scale makes it a challenge to implement such a system. This system utilizes some new methods to deal with the issue of imprecise musical scale of input voice of a human singer, such as spectral standard deviation used for note segmentation, Adaptive Round Semitone used for melody tracking and Tune Map acting as a musical grammar constraint in melody tracking. Furthermore, a large vocabulary speech recognizer performing the lyric recognition tasks is also added, which is a new trial in a singing transcription system.
Adaptive model predictive control for constrained linear systems

A novel adaptive output feedback control technique for uncertain linear systems is proposed, able to cope with input and output constraints and measurement noise. At each time step, the collected input-output data are exploited to refine the set of models that are consistent with the available information on the system. Then, the control input is computed according to a receding horizon strategy, which guarantees recursive constraint satisfaction for all the admissible models, hence also for the actual plant. The technique relies only on the solution of linear and quadratic programs. The effectiveness of the approach is illustrated in a numerical example.
Antitumorigenic Effects of Peroxisome Proliferator-Activated Receptor-γ in Non-Small-Cell Lung Cancer Cells Are Mediated by Suppression of Cyclooxygenase-2 via Inhibition of Nuclear Factor-κB

Pharmacological activators of peroxisome proliferator-activated receptor-γ (PPARγ) inhibit growth of non-small-cell lung cancer (NSCLC) cell lines in vitro and in xenograft models. Because these agents engage off-target pathways, we have assessed the effects of PPARγ by overexpressing the protein in NSCLC cells. We reported previously that increased PPARγ inhibits transformed growth and invasiveness and promotes epithelial differentiation in a panel of NSCLC expressing oncogenic K-Ras. These cells express high levels of cyclooxygenase-2 (COX-2) and produce high levels of prostaglandin E2 (PGE2). The goal of these studies was to identify the molecular mechanisms whereby PPARγ inhibits tumorigenesis. Increased PPARγ inhibited expression of COX-2 protein and promoter activity, resulting in decreased PGE2 production. Suppression of COX-2 was mediated through increased activity of the tumor suppressor phosphatase and tensin homolog, leading to decreased levels of phospho-Akt and inhibition of nuclear factor-κB activity. Pharmacological inhibition of PGE2 production mimicked the effects of PPARγ on epithelial differentiation in three-dimensional culture, and exogenous PGE2 reversed the effects of increased PPARγ activity. Transgenic mice overexpressing PPARγ under the control of the surfactant protein C promoter had reduced expression of COX-2 in type II cells and were protected against developing lung tumors in a chemical carcinogenesis model. These data indicate that high levels of PGE2 as a result of elevated COX-2 expression are critical for promoting lung tumorigenesis and that the antitumorigenic effects of PPARγ are mediated in part through blocking this pathway.
Natural Products as Lead Compounds for Sodium Glucose Cotransporter (SGLT) Inhibitors

Abstract Glucose homeostasis is maintained by antagonistic hormones such as insulin and glucagon as well as by regulation of glucose absorption, gluconeogenesis, biosynthesis and mobilization of glycogen, glucose consumption in all tissues and glomerular filtration, and reabsorption of glucose in the kidneys. Glucose enters or leaves cells mainly with the help of two membrane integrated transporters belonging either to the family of facilitative glucose transporters (GLUTs) or to the family of sodium glucose cotransporters (SGLTs). The intestinal glucose absorption by endothelial cells is managed by SGLT1, the transfer from them to the blood by GLUT2. In the kidney SGLT2 and SGLT1 are responsible for reabsorption of filtered glucose from the primary urine, and GLUT2 and GLUT1 enable the transport of glucose from epithelial cells back into the blood stream. The flavonoid phlorizin was isolated from the bark of apple trees and shown to cause glucosuria. Phlorizin is an inhibitor of SGLT1 and SGLT2. With phlorizin as lead compound, specific inhibitors of SGLT2 were developed in the last decade and some of them have been approved for treatment mainly of type 2 diabetes. Inhibition of SGLT2 eliminates excess glucose via the urine. In recent times, the dual SGLT1/SGLT2 inhibitory activity of phlorizin has served as a model for the development and testing of new drugs exhibiting both activities. Besides phlorizin, also some other flavonoids and especially flavonoid enriched plant extracts have been investigated for their potency to reduce postprandial blood glucose levels which can be helpful in the prevention and supplementary treatment especially of type 2 diabetes.
Normalization of “Second Wives”: Gender Contestation in Hong Kong

This paper discusses the recent phenomenon of bau yilai (literatly "keeping second wives") is Hong Kong as the city becomes the nexus of South Chinas economic expansion. An increasing number of Hong Kong men have established extra-marital relationships across the border with mainland Chinese women. This new form of polygyny is believed to be extremely widespread non-class specific and defying geographical restriction almost second nature to male migrant capital and labor. The debate on the bau yilai phenomenon has a markedly moral undertone. Ironically the female campain to contest the perceived revival of polygyny resulted in its normalization. What was to be a re-evaluation of the institutions of marriage and family soon became a reinforcement of their patriarchal foundation. And as the phenomenon became commercially exploited and consumed everyday as various forms of popular culture the illegal yilai relationships came to shed off its abnormality. This change shows that in the transitional period to 1997 Hong Kongs relationship with China interplays with the construction of individual identities in a fluid cultural milieu manifested in the gendered negotiations and interpretations of their future. (authors)
Diabetes Genes and Prostate Cancer in the Atherosclerosis Risk in Communities Study

There is a known inverse association between type 2 diabetes (T2D) and prostate cancer (PrCa) that is poorly understood. Genetic studies of the T2D-PrCa association may provide insight into the underlying mechanisms of this association. We evaluated associations in the Atherosclerosis Risk in Communities study between PrCa and nine T2D single nucleotide polymorphisms from genome-wide association studies of T2D (in CDKAL1, CDKN2A/B, FTO, HHEX, IGF2BP2, KCNJ11, PPARG, SLC30A8, and TCF7L2) and four T2D single nucleotide polymorphisms from pre–genome-wide association studies (in ADRB2, CAPN10, SLC2A2, and UCP2). From 1987 to 2000, there were 397 incident PrCa cases among 6,642 men ages 45 to 64 years at baseline. We used race-adjusted Cox proportional hazards models to estimate associations between PrCa and increasing number of T2D risk-raising alleles. PrCa was positively associated with the CAPN10 rs3792267 G allele [hazard ratio (HR) 1.20; 95% confidence interval (CI), 1.00-1.44] and inversely associated with the SLC2A2 rs5400 Thr110 allele (HR, 0.85; 95% CI, 0.72, 1.00), the UCP2 rs660339 Val55 allele (HR, 0.84; 95% CI, 0.73, 0.97) and the IGF2BP2 rs4402960 T allele (HR, 0.79; 95% CI, 0.61-1.02; blacks only). The TCF7L2 rs7903146 T allele was inversely associated with PrCa using a dominant genetic model (HR, 0.79; 95% CI, 0.65-0.97). Further knowledge of T2D gene-PrCa mechanisms may improve understanding of PrCa etiology. Cancer Epidemiol Biomarkers Prev; 19(2); 558–65
Leader-Follower Formations: Uncalibrated Vision-Based Localization and Control

This paper focuses on leader-follower formations of mobile robots equipped with panoramic cameras and extend earlier works in the literature addressing both the vision-based localization and control problems. First, a new sufficient analytical condition for localizability is proved and used to shed light on the geometrical meaning of formation localization using uncalibrated vision sensors, here performed with the unscented Kalman filter. Second, we design a feedback control law based on dynamic extension in order to extend the applicability of our control scheme also to the case of distant robots.
Fuzzy Measure Extraction for Software Quality Assessment as a Multi-Criteria Decision-Making Problem

Being able to assess software quality is essential as software is ubiquitous in every aspect of our day-to-day lives. In this paper, we rely on existing research and metrics for defining software quality and propose a way to automatically assess software quality based on these metrics. In particular, we show that the software quality assessment problem can be viewed as a multi-criteria decision-making (MCDM) problem. In Multi-Criteria Decision Making (MCDM), decisions are based on several criteria that are usually conflicting and non-homogenously satisfied. Non-additive (fuzzy) measures along with the Choquet integral can be used: they model and aggregate the levels of satisfaction of these criteria by considering their relationships. However, in practice, it is difficult to identify such fuzzy measures. An automated process is necessary and can be used when sample data is available. We propose to automatically assess software by modeling experts’ decision process: to do this we automatically extract the corresponding fuzzy measure from samples of the target experts’ decision. We were able to improve previous approaches to automatic software quality assessment that used machine learning techniques.
Wireless indoor channel modeling: statistical agreement of ray tracing simulations and channel sounding measurements

A statistical space-time model for indoor wireless propagation based on empirical measurements is compared with results from the deterministic ray-tracing simulation tool WiSE for the same environment. Excellent agreement is found in terms of the distributions of arrival times and angular spread for both modeling approaches. The WiSE package is also use to synthesize MIMO channel matrices and determine the theoretical capacity, available in the tested environments. It is found that, for narrowband channels, the spatial clustering of the multipaths limits the capacity gains associated with increased array size.
Developments to the BackPropagation Learning Algorithm .

The original back-propagation methods were plagued with variable parameters which affected both the convergence properties of the training and the generalisation abilities of the resulting network. These parameters presented many difficulties when attempting to use these networks to solve particular mapping problems. A combination of established numerical minimisation methods (Polak-Ribiere Conjugate gradient descent) with a novel idea for stepping out of local minima has produced a network minimisation package which is self optimising and has essentially no free parameters.
Extending the EPCIS with Building Automation Systems: A New Information System for the Internet of Things

Electronic Product Code Information System (EPCIS) has been a well-known information system for tracking and monitoring physical objects' life-cycle using RFID technology. However, in the Internet of Things (IoT) context, physical objects are supposed to be equipped with computing and sensing capability. Thus, people are interested not only in objects' life-cycle but also their contextual data. This emerging issue poses a new functional requirement on the traditional EPCIS such that, objects' contextual data should also be managed along with their life-cycle. Meanwhile, one of the most important IoT application lays in Building Automation Systems where smart devices are connected and automated without human intervention. These devices usually generate a large volume of data in a daily basis and thus, designing a proper data warehousing for this use case becomes a challenge. This paper aims at adding a data capturing interface to the traditional EPCIS so that it can support objects' data storage and retrieval, thus seamlessly adds significant support for Building Automation Systems application. The extended system, which is called Smart Thing Information System (STIS), exploits the oBIX standard and CoAP protocol to capture the data send from the smart devices and provides an additional lightweight query interface also based on CoAP. The system's applicability has been verified through a practical global-wide test bed between Korea and Austria.