Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolution of neural network training set through addition of virtual samples

Using an oversized neural network or too small a training sample set results in overfitting. In order to improve generalization capability, either the network should be reduced or additional training samples have to be collected. Obtaining additional training samples, however, can be often very expensive or impossible. Here we propose an evolutionary approach where new virtual samples are added to the training sample set as a population of MLPs evolve over generations. At each generation, these newly added virtual samples are used to retrain the MLPs. This approach is in contrast to previous evolutionary neural network approaches where connection weights, network architectures, learning rules, or their mixtures evolve. A preliminary result obtained from a robot arm kinematics problem is promising. The generalization error was reduced more than 50%. The approach can be applied in various practical situations where additional training samples are expensive or impossible.
Efficient Extraction of Agarose from Red Algae Using Ionic Liquids

We explored the possibility of using ionic liquids (ILs) as medium for efficient extraction of agarose via dissolution of red algae under varying conditions of heating or microwave irradiation. As compared to conventional methods, a very high extraction yield of good quality agarose (as high as 39 wt%) could be achieved depending upon the nature of used IL and applied experimental conditions. Purity of extracted agarose was confirmed from various spectral and analytical techniques, such as 1H and 13C NMR, FTIR, circular dichroism (CD), gel permeation chromatography (GPC) and thermogravimetric analysis (TGA). The physicochemical properties, such as gelling or melting temperature, viscosity and gel strength of extracted agarose hydrogels have been measured and compared with the agarose obtained from similar source reported in the literature. ILs were recovered after the extraction of agarose and were reused for further extraction experiments. % Recycling and extraction ability of recycled ILs in different cycles have been measured. The developed extraction process of utilizing ILs as medium is easy, simple and highly efficient as compared to the conventional methods of agarose extraction from algae.
Trithorax- and Polycomb-Group Response Elements within an Ultrabithorax Transcription Maintenance Unit Consist of Closely Situated but Separable Sequences

ABSTRACT In Drosophila, two classes of genes, thetrithorax group and the Polycomb group, are required in concert to maintain gene expression by regulating chromatin structure. We have identified Trithorax protein (TRX) binding elements within the bithorax complex and have found that within thebxd/pbx regulatory region these elements are functionally relevant for normal expression patterns in embryos and confer TRX binding in vivo. TRX was localized to three closely situated sites within a 3-kb chromatin maintenance unit with a modular structure. Results of an in vivo analysis showed that these DNA fragments (each ∼400 bp) contain both TRX- and Polycomb-group response elements (TREs and PREs) and that in the context of the endogenousUltrabithorax gene, all of these elements are essential for proper maintenance of expression in embryos. Dissection of one of these maintenance modules showed that TRX- and Polycomb-group responsiveness is conferred by neighboring but separable DNA sequences, suggesting that independent protein complexes are formed at their respective response elements. Furthermore, we have found that the activity of this TRE requires a sequence (∼90 bp) which maps to within several tens of base pairs from the closest neighboring PRE and that the PRE activity in one of the elements may require a binding site for PHO, the protein product of the Polycomb-group genepleiohomeotic. Our results show that long-range maintenance of Ultrabithorax expression requires a complex element composed of cooperating modules, each capable of interacting with both positive and negative chromatin regulators.
Intensifying Platelet Inhibition With Tirofiban in Poor Responders to Aspirin, Clopidogrel, or Both Agents Undergoing Elective Coronary Intervention: Results From the Double-Blind, Prospective, Randomized Tailoring Treatment With Tirofiban in Patients Showing Resistance to Aspirin and/or Resistance 

Background— Inhibition of platelet aggregation after aspirin or clopidogrel intake varies greatly among patients, and previous studies have suggested that poor response to oral antiplatelet agents may increase the risk of thrombotic events, especially after coronary angioplasty. Whether this reflects suboptimal platelet inhibition per se, which might benefit from more potent antiplatelet agents such as tirofiban, is unknown. Methods and Results— We screened 1277 patients to enroll 93 aspirin, 147 clopidogrel, and 23 dual poor responders, based on a point-of-care assay, who underwent elective coronary angioplasty at 10 European sites for stable or low-risk unstable coronary artery disease. Patients were randomly assigned in a double-blind manner to receive either tirofiban (n=132) or placebo (n=131) on top of standard aspirin and clopidogrel therapy. The primary end point, consisting of troponin I/T elevation at least 3 times the upper limit of normal, was attained in 20.4% (n=27) in the tirofiban group compared with 35.1% (n=46) in the placebo group (relative risk, 0.58; 95% confidence interval, 0.39 to 0.88; P=0.009). The rate of major adverse cardiovascular events within 30 days in the tirofiban group also was reduced (3.8% versus 10.7%; P=0.031). The overall incidence of bleeding was low, likely explained by a substantial use of the transradial approach, and did not differ between the 2 groups. Conclusions— In low-risk patients according to clinical presentation who had poor responsiveness to standard oral platelet inhibitors via a point-of-care assay, intensified platelet inhibition with tirofiban lowers the incidence of myocardial infarction after elective coronary intervention.
A Process to Analyze Strategic Design and Management Decisions Under Uncertainty in Complex Entrepreneurial Systems

This paper proposes a process to support strategic design and management of complex entrepreneurial systems under uncertainty. The process is designed to help designers and decisions‐makers readily identify valuable opportunities for flexibility as a way to deal pro‐actively with uncertainty and improve strategically the lifecycle performance of the system as it is designed, deployed, and managed in operations. The process relies on the novel concept of a layered design structure matrix (DSM), which provides gradually a systems‐level representation of the enterprise system starting at an early stage, and gaining more details as more information becomes available about the system and its environment. The resulting layered DSM is used to identify performance‐enhancing flexibility strategies in the design and management of the system. The flexibility, providing the “right, but not the obligation, to change the system in the face of uncertainty” provides contingencies to minimize exposure to downside risks, and to enable the system to capture upside opportunities—thereby improving expected lifecycle performance. The process is applied as a demonstration to the analysis of a startup system in the sector of mobility on‐demand transportation. Strategic‐level opportunities for flexibility are identified systematically, and real options analysis is used to demonstrate quantitatively lifecycle performance improvement as compared to baseline design concepts.
Threats and Countermeasures on a 4G Mobile Network

The appearance of high performance smartphones and increasing mobile services, enabled by the advancement of mobile phones and mobile communication technology, changed the mobile communication network architecture from a closed type to open type. In the open type network, anyone can access the network and various attacks and abnormal traffic can penetrate it, but existing IP based security technologies cannot block them. Particularly, there is no technology to detect the protocols such as GTP (GPRS Tunneling Protocol) specialized to the mobile communication network in the high volume traffic processing environment in the 4G mobile network. This paper describes the various types of threats to 4G mobile networks and measures to cope with them.
Cost-Effectiveness of Single-Level Anterior Cervical Discectomy and Fusion for Cervical Spondylosis

Study Design. Cost-effectiveness analysis with retrospective cost analysis and literature review. Objective. To determine the relative cost-effectiveness of anterior cervical discectomy and fusion (ACDF) with autograft, allograft, and allograft with plating for single-level anterior cervical spondylosis. Summary of Background Data. There are several accepted methods of surgically treating single-level cervical spondylosis anteriorly. No study has clearly demonstrated the superiority of one method over the alternatives. The techniques may differ in their operative risks and resource use, perioperative complications, short-term outcome, and long-term outcome and complications. Formal cost-effectiveness analysis (CEA) provides a structure for analyzing many variables and comparing different treatment outcomes. Sensitivity analysis is used to test the robustness of the model and to determine variables that have significant effects on the results. Future areas of research and refinements of the CEA model can be developed from these findings. Methods. A retrospective review of hospital charges was performed for 78 patients who underwent single-level ACDF with allograft alone or ACDF with allograft and plating (ACDFP). The charges were converted to estimated costs for fiscal year 2000 using the ratio of costs to charges method. A CEA model was developed consisting of a decision-analysis model for the first year postsurgery and a Markov model for the next 4 years after surgery. Probabilities and outcome utilities were estimated from the literature. Outcome was measured in quality-adjusted life years (QALYs), and incremental CEA was performed. Several variables were tested in one-way sensitivity analysis. Results. Compared with ACDF with autograft, ACDF with allograft offered an improvement in quality of life at a cost of $496 per QALY. ACDFP provided additional gains in quality of life compared with ACDF with allograft at a cost of $32,560 per QALY in the base case analysis. In sensitivity analysis, these estimates varied between $417 and $741 per QALY and between $19,090 per QALY and domination of ACDFP by ACDF with allograft, respectively. The results were most sensitive to assumptions regarding differences in the length of the postoperative recovery period. Conclusions. ACDF with allograft offers a benefit relative to ACDF with autograft at a cost of $496 per QALY. ACDFP has a benefit relative to ACDF with allograft at an approximate cost of $32,560 per QALY. CEA provides a method for comparing the benefits and risks of these three procedures. Further research needs to be performed regarding these procedures, particularly examining the postoperative recovery period.
Unique Allelic eQTL Clusters in Human MHC Haplotypes

The control of gene regulation within the major histocompatibility complex (MHC) remains poorly understood, despite several expression quantitative trait loci (eQTL) studies revealing an association of MHC gene expression with independent tag-single nucleotide polymorphisms (SNPs). MHC haplotype variation may exert a greater effect on gene expression phenotype than specific single variants. To explore the effect of MHC haplotype sequence diversity on gene expression phenotypes across the MHC, we examined the MHC transcriptomic landscape at haplotype-specific resolution for three prominent MHC haplotypes (A2-B46-DR9, A33-B58-DR3, and A1-B8-DR3) derived from MHC-homozygous B-lymphoblastoid cell lines (B-LCLs). We demonstrate that MHC-wide gene expression patterns are dictated by underlying haplotypes, and identify 36 differentially expressed genes. By mapping these haplotype sequence variations to known eQTL, we provide evidence that unique allelic combinations of eQTL, embedded within haplotypes, are correlated with the level of expression of 17 genes. Interestingly, the influence of haplotype sequence on gene expression is not homogenous across the MHC. We show that haplotype sequence polymorphisms within or proximate to HLA-A, HLA-C, C4A, and HLA-DRB regions exert haplotype-specific gene regulatory effects, whereas the expression of genes in other parts of the MHC region are not affected by the haplotype sequence. Overall, we demonstrate that MHC haplotype sequence diversity can impact phenotypic outcome via the alteration of transcriptional variability, indicating that a haplotype-based approach is fundamental for the assessment of trait associations in the MHC.
Integration of transcription factor binding and gene expression by associative clustering

We integrate paired genomic data sets to reveal their dependencies. We suggest using a dependency-maximizing clustering method for the task. The recently introduced method associative clustering (AC) finds groupings of genes for which the two data sources are maximally dependent. The dependencies between data sources become represented as a contingency table, which is optimized to reveal the association between data sets, bypassing the possible incommensurability between the data sets. The method is applied to searching for regulatory interactions in yeast, by looking for dependencies between gene expression profiles and regulator binding patterns.
Achieving privacy and security in radio frequency identification

Radio Frequency Identification RFID systems are gaining popularity in a wide variety of applications like asset tracking, personnel identification, and sensor networks. However, unique security and privacy issues arise in these systems because (a) low computation capabilities of RFID tags prevent the use of complicated cryptographic protocols, and (b) wide deployment of tags opens up room for illegal tracking of people and objects. In this paper, we first describe a basis-set of requirements that need to be necessarily satisfied to mitigate security and privacy problems in RFID systems. We then outline some recent proposals that try to solve these issues, and then explore in detail a research publication [1] that uses a pseudonym based tree walking security scheme [2], and claims to meet all the requirements. However, we identify some attacks that are still possible in this scheme [1] in the same threat model but more realistic scenarios, and then extend the scheme to mitigate these attacks. We also address the issue of secure establishment of session keys to exchange information between tags, readers, and centralized trusted centers, which had not been proposed earlier. Our extensions make the overall scheme complete, and deal with most issues that had not been addressed comprehensively by other related work in the past. In all, our extensions provide a complete RFID scheme that meets all the security and privacy goals.
Exploring the Use of Podcasts and Vodcasts: Multimedia Tools for Word Learning

The study investigated the impact of podcasts and vodcasts accessed through an iPod on fourth- and sixth-grade students’ vocabulary acquisition. Students were randomly assigned to either a podcast group or a vodcast group. Regardless of group assignment, each student completed three six-minute podcasts or vodcasts a day for three days. On average, students learned four out of nine words taught regardless of group assignment. The vodcast group learned significantly more words compared to the podcast group at the receptive level and at the expressive level. Student comments indicated that iPods should be used to teach and to review words.
A trace-scaling agent for parallel application tracing

Tracing and performance analysis tools are an important component in the development of high performance applications. Tracing parallel programs with current tracing tools, however, easily leads to large trace files with hundreds of Megabytes. The storage, visualization, and analysis of such trace files is often difficult. We propose a trace-scaling agent for tracing parallel applications, which learns the application behavior in runtime and achieves a small, easy to handle trace. The agent dynamically identifies the amount of information needed to capture the application behavior. This knowledge acquired at runtime allows recording only the non-iterative trace information, which drastically reduces the size of the trace file.
Assessment of Suicidal Behaviors and Risk Among Children and Adolescents

An online listing of interview, self-report, and screening tools for assessing suicide in children and adolescents, including behaviors, risk, intentionality, attitudes, reasons, exposure to suicide, and other factors. Includes psychometric properties, where to obtain the instrument, and references. Reproduced from a technical report submitted to the National Institute of Mental Health by D. Goldston (2000).
An Exercise and Education Program Improves Well-Being of New Mothers: A Randomized Controlled Trial

Objective The purpose of this study was to evaluate the effect of a physical therapy exercise and health care education program on the psychological well-being of new mothers. Design This was a randomized controlled trial. Participants Primiparous and multiparous English-speaking women ready for discharge from The Angliss Hospital postnatal ward were eligible for this study. Women who were receiving psychiatric care were excluded. One hundred sixty-one women were randomized into the trial. Intervention The experimental group (n=62) received an 8-week “Mother and Baby” (M&B) program, including specialized exercise provided by a women's health physical therapist combined with parenting education. The other group (education only [EO], n=73) received only the same educational material as the experimental group. Main Outcome Measures Psychological well-being (Positive Affect Balance Scale), depressive symptoms (Edinburgh Postnatal Depression Scale), and physical activity levels were assessed at baseline, after 8 weeks (post-program), and then 4 weeks later. Results There was significant improvement in well-being scores and depressive symptoms of the M&B group compared with the EO group over the study period. More specifically, there was a significant positive effect on well-being scores and depressive symptoms at 8 weeks, and this effect was maintained 4 weeks after completion of the program. The number of women identified as “at risk” for postnatal depression pre-intervention was reduced by 50% by the end of the intervention. Limitations Although this study provides promising short-term (4-week) outcomes, further work is needed to explore whether the intervention effects are maintained as sustained psychological and behavioral benefits at 6 months. Conclusions A physical therapy exercise and health education program is effective in improving postnatal well-being. Routine use of this program may reduce longer-term problems such as postnatal depression.
Common threshold in quantile regressions with an application to pricing for reputation

Abstract The paper develops a systematic estimation and inference procedure for quantile regression models where there may exist a common threshold effect across different quantile indices. We first propose a sup-Wald test for the existence of a threshold effect, and then study the asymptotic properties of the estimators in a threshold quantile regression model under the shrinking threshold effect framework. We consider several tests for the presence of a common threshold value across different quantile indices and obtain their limiting distributions. We apply our methodology to study the pricing strategy for reputation through the use of a data set from Taobao.com. In our economic model, an online seller maximizes the sum of the profit from current sales and the possible future gain from a targeted higher reputation level. We show that the model can predict a jump in optimal pricing behavior, which is considered as “reputation effect” in this paper. The use of threshold quantile regression model allows us to identify and explore the reputation effect and its heterogeneity in data. We find both reputation effects and common thresholds for a range of quantile indices in seller’s pricing strategy in our application.
Anatomical Brain Images Alone Can Accurately Diagnose Chronic Neuropsychiatric Illnesses

Objective Diagnoses using imaging-based measures alone offer the hope of improving the accuracy of clinical diagnosis, thereby reducing the costs associated with incorrect treatments. Previous attempts to use brain imaging for diagnosis, however, have had only limited success in diagnosing patients who are independent of the samples used to derive the diagnostic algorithms. We aimed to develop a classification algorithm that can accurately diagnose chronic, well-characterized neuropsychiatric illness in single individuals, given the availability of sufficiently precise delineations of brain regions across several neural systems in anatomical MR images of the brain. Methods We have developed an automated method to diagnose individuals as having one of various neuropsychiatric illnesses using only anatomical MRI scans. The method employs a semi-supervised learning algorithm that discovers natural groupings of brains based on the spatial patterns of variation in the morphology of the cerebral cortex and other brain regions. We used split-half and leave-one-out cross-validation analyses in large MRI datasets to assess the reproducibility and diagnostic accuracy of those groupings. Results In MRI datasets from persons with Attention-Deficit/Hyperactivity Disorder, Schizophrenia, Tourette Syndrome, Bipolar Disorder, or persons at high or low familial risk for Major Depressive Disorder, our method discriminated with high specificity and nearly perfect sensitivity the brains of persons who had one specific neuropsychiatric disorder from the brains of healthy participants and the brains of persons who had a different neuropsychiatric disorder. Conclusions Although the classification algorithm presupposes the availability of precisely delineated brain regions, our findings suggest that patterns of morphological variation across brain surfaces, extracted from MRI scans alone, can successfully diagnose the presence of chronic neuropsychiatric disorders. Extensions of these methods are likely to provide biomarkers that will aid in identifying biological subtypes of those disorders, predicting disease course, and individualizing treatments for a wide range of neuropsychiatric illnesses.
Document representation with Generalized Latent Semantic Analysis

Methods for dimensionality reduction, notably LSA, have been successfully applied to the information retrieval task and document classification. Recently, corpus-based association measures such as point-wise mutual information have been found to outperform LSA on a variety of tasks. We have developed an algorithmic framework that computes a low-dimensional vector space representation of documents combining different measures of association with different dimensionality reduction techniques. Experimental results show a competitive performance on the synonymy and text classification tasks.