Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-Reactivity, Epitope Spreading, and De Novo Immune Stimulation Are Possible Mechanisms of Cross-Protection of Nonvaccine Human Papillomavirus (HPV) Types in Recipients of HPV Therapeutic Vaccines

ABSTRACT Numerous versions of human papillomavirus (HPV) therapeutic vaccines designed to treat individuals with established HPV infection, including those with cervical intraepithelial neoplasia (CIN), are in development because approved prophylactic vaccines are not effective once HPV infection is established. As human papillomavirus 16 (HPV-16) is the most commonly detected type worldwide, all versions of HPV therapeutic vaccines contain HPV-16, and some also contain HPV-18. While these two HPV types are responsible for approximately 70% of cervical cancer cases, there are other high-risk HPV types known to cause malignancy. Therefore, it would be of interest to assess whether these HPV therapeutic vaccines may confer cross-protection against other high-risk HPV types. Data available from a few clinical trials that enrolled subjects with CINs regardless of the HPV type(s) present demonstrated clinical responses, as measured by CIN regression, in subjects with both vaccine-matched and nonvaccine HPV types. The currently available evidence demonstrating cross-reactivity, epitope spreading, and de novo immune stimulation as possible mechanisms of cross-protection conferred by investigational HPV therapeutic vaccines is discussed.
Implementation of an ODM and HL7 Compliant Electronic Patient-Reported Outcome System

Interoperability is one of the biggest issues in health informatics despite of the huge effort invested to solve it. Clinical Data Interchange Standards Consortium (CDISC) and Health Level 7 (HL7) are two of the most recognized institutions working on this field. Several systems are becoming compliant with their standards; however, the process to accomplish it is not always straightforward. In this manuscript, we present the successful implementation of the CDISC ODM and HL7 import and export functions for "MoPat", a web-based multi-language electronic patient-reported outcomes system. The system has been evaluated and tested and is currently being used for clinical study and routine data collection, including more than 10.000 patient encounters.
Figure analysis: A teaching technique to promote visual literacy and active Learning

Learning often improves when active learning techniques are used in place of traditional lectures. For many of these techniques, however, students are expected to apply concepts that they have already grasped. A challenge, therefore, is how to incorporate active learning into the classroom of courses with heavy content, such as molecular‐based biology courses. An additional challenge is that visual literacy is often overlooked in undergraduate science education. To address both of these challenges, a technique called figure analysis was developed and implemented in three different levels of undergraduate biology courses. Here, students learn content while gaining practice in interpreting visual information by discussing figures with their peers. Student groups also make connections between new and previously learned concepts on their own while in class. The instructor summarizes the material for the class only after students grapple with it in small groups. Students reported a preference for learning by figure analysis over traditional lecture, and female students in particular reported increased confidence in their analytical abilities. There is not a technology requirement for this technique; therefore, it may be utilized both in classrooms and in nontraditional spaces. Additionally, the amount of preparation required is comparable to that of a traditional lecture. © 2016 by The International Union of Biochemistry and Molecular Biology, 44(4):336–344, 2016.
Multi-region DCIV spectroscopy and impacts on the design of STI-based LDMOSFETs

A probing technique, multi-region DCIV spectroscopy, has been investigated systematically. This non-destructive method demonstrated the attractive capability on profiling the interface states overall in STI-based LDMOSFETs. The sensitivity on the interface state generation at channel and accumulation region was superior to the conventional Id-Vg method. Based on the device characterization and stress tests, the dependence of spectroscopic features on channel, accumulation and poly overlap length was investigated and verified. The optimum device design to suppress device degradation was proposed.
Treatment of Esophageal Cancer Based on Histology: A Surveillance Epidemiology and End Results Analysis

Introduction:The majority of esophageal cancer is either adenocarcinoma (ACA) or squamous cell carcinoma (SCCA). Recent randomized trials suggest that definitive chemoradiotherapy may be equally effective as surgery. However, the responsiveness of ACA versus SCCA to radiotherapy (RT) has never been compared. This Surveillance Epidemiology and End Results registry analysis investigates whether survival differed between ACA and SCCA based on the treatment modality. Methods:Patients with T2-4N0 or N+ SCCA and ACA in the cervical or thoracic esophagus diagnosed from 1983 to 2004 were obtained from the Surveillance Epidemiology and End Results database. Patients with multiple primary cancers, underwent a surgical procedure other than partial or total esophagectomy, had metastatic or T1N0 disease, or received RT that did not include external beam radiation were excluded. Patients were grouped according to treatment received: RT alone, preoperative RT, any surgery (regardless of use of RT), and surgery alone. Results:A total of 4752 patients were included, 2680 (56%) had ACA and 2072 (44%) had SCCA. After adjusting for age, marital status, cost of living, and race, the overall survival (OS) and cause-specific survival was similar for all treatment groups except the RT-alone group where OS and SCC were superior for ACA. However, no difference in 3- and 5-year OS and cause-specific survival rates for all groups. Conclusions:No difference in survival was seen between patients with ACA and SCCA across any of the major treatment modalities for esophageal cancer, suggesting that both histologies respond to treatment similarly.
Clinical Tests of Therapeutical Failures Based on Mathematical Modeling of the HIV Infection

Clinical tests which are displayed are based on a system-theoretic approach for an early diagnosis of the immunological and virological failure of HIV patients. Mathematical characterizations of therapeutical failures are presented in this paper. Mathematical modeling is used for individual patients to help for an early diagnosis of the evolution of the infection. The feasibility of the method is depicted on some patients who start highly active antiretroviral therapy (HAART). The identifiability of the continuous-time models which are used is proved, and it is shown to be invariant under discretization.
Molecular phylogeny of Loliginidae inferred from mitochondrial DNA sequence variation

Abstract Loliginidae includes many economically important species in trophic systems worldwide. Here, we investigated genetic relationships and diversity in this family. Sequence comparisons and phylogenetic analyses revealed considerable variations between mitochondrial 16 S rRNA gene and cytochrome coxidase subunit I gene among nine Loliginid species. We identified three similar non-coding regions in eight Loliginid species, but not in Sepioteuthislessoniana. We detected a single extended termination-associated sequence and three conserved sequence blocks among these eight species. Our results suggest that Loliginidae forms a major lineage, with S. lessoniana located at the most basal position and forming an individual clade as sister to the remaining species. Loligobeka, Loliolusjaponica, Loliolusuyii, Loligochinensis, Loligoedulis, Loligoduvauceli, Loligobleekeri, and Loligoopalescensare clustered into a monophyletic group. We identified repetitive elements and repeat numbers in the control regions.
Second-order filter response from parallel coupled glass microring resonators

Ring resonators are coupled in parallel in order to obtain a second order type of wavelength response. The phase relationship between the rings determines the details of the spectral response. The rings used in the experiment have radii of 25 /spl mu/m and are fabricated from compound glass having an index of 1.539. Several resonances are observed to have double peaked box-like response.
The adaptive predictive function control based on Laguerre model

A new strategy of adaptive predictive function control based on Laguerre model is developed. The parameters of Laguerre model are identified by the recursive least square method with forgetting factor. Based on the identified result, the adaptive predictive function controller (PFC) is designed. The result of simulation shows the performance of the derived control strategy.
Network Coding for 5G Network and D2D Communication

Unlike traditional routing where packets are only stored and forward, network coding allows packets to mix together. New packets can be formed by combining other packets. This technique can provide benefits to the network. Network coding has been shown to improve network throughput, reduce energy consumption, improve network robustness and achieve the network capacity. 5G Network is foreseen as a novel network paradigm enabling massive device connectivity and enabling device-to-device communication (D2D). It has many potential applications ranging from ultra high definition video to virtual reality applications. In this paper, we present the advantages, benefits, scenarios, and applications of Network coding for 5G Network and device-to-device communication. We present the state-of-art research, the theoretical benefits, and detail how network coding can improve 5G Networks and D2D communication. Our results show that network coding can almost double the network throughput while increasing network robustness and decreasing the overall time to disseminate messages.
Spatiotemporal modeling of 2000–2009 financial development in Yangtze River Delta using support vector machine and clustering analysis

Over the past decade, the Yangtze River Delta has witnessed a financial takeoff. Its mechanism need be understood. The paper attempts to integrate a number of analytic methods to model the financial development of 16 cities in the region from 2000 to 2009. A set of indicators describing the economic environment, foreign trade conditions, banking and insurance industry, and urban development are first identified, with the financial interrelations ratio being selected to represent financial development. Then, the time series data of each city are used to build a temporal model under the theoretical framework of SVM. In the model, the method of cross-validation is introduced for choosing the best parameter of the kernel function and the penalty coefficient to be used later in model training and regression. In the final analysis, the time series data of each city are analyzed through clustering, showing the dynamics of the cities during 2000–2009.
Asynchronous hybrid maximum likelihood classification of linear modulations

In this paper, we consider the problem of linear modulation classification in the presence of unknown time offset, phase offset and received signal amplitude. We develop a novel hybrid maximum likelihood (HML) approach based on a Generalized Expectation Maximization (GEM) algorithm [1]. Our approach is applicable to all QAM and PSK modulations, and it does not require any assumptions on the received signal-to-noise ratio (SNR). The GEM algorithm provides a tractable procedure to obtain maximum likelihood (ML) estimates which are extremely hard to obtain otherwise. Moreover, our approach employs only a small number of samples (in the order of hundreds) to perform both time and phase synchronization, signal power estimation, followed by modulation classification. The proposed approach also enables maximum a posteriori (MAP) decoding of the unknown constellation symbol sequence as a by-product of the GEM algorithm. We provide simulation results that show that the proposed approach provides excellent classification performance.
Research Paper: Generating a Reliable Reference Standard Set for Syndromic Case Classification

OBJECTIVE To generate and measure the reliability for a reference standard set with representative cases from seven broad syndromic case definitions and several narrower syndromic definitions used for biosurveillance. DESIGN From 527,228 eligible patients between 1990 and 2003, we generated a set of patients potentially positive for seven syndromes by classifying all eligible patients according to their ICD-9 primary discharge diagnoses. We selected a representative subset of the cases for chart review by physicians, who read emergency department reports and assigned values to 14 variables related to the seven syndromes. MEASUREMENTS (1) Positive predictive value of the ICD-9 diagnoses; (2) prevalence of the syndromic definitions and related variables; (3) agreement between physician raters demonstrated by kappa, kappa corrected for bias and prevalence, and Finn's r; and (4) reliability of the reference standard classifications demonstrated by generalizability coefficients. RESULTS Positive predictive value for ICD-9 classification ranged from 0.33 for botulinic to 0.86 for gastrointestinal. We generated between 80 and 566 positive cases for six of the seven syndromic definitions. Rash syndrome exhibited low prevalence (34 cases). Agreement between physician raters was high, with kappa > 0.70 for most variables. Ratings showed no bias. Finn's r was >0.70 for all variables. Generalizability coefficients were >0.70 for all variables but three. CONCLUSION Of the 27 syndromes generated by the 14 variables, 21 showed high enough prevalence, agreement, and reliability to be used as reference standard definitions against which an automated syndromic classifier could be compared. Syndromic definitions that showed poor agreement or low prevalence include febrile botulinic syndrome, febrile and nonfebrile rash syndrome, respiratory syndrome explained by a nonrespiratory or noninfectious diagnosis, and febrile and nonfebrile gastrointestinal syndrome explained by a nongastrointestinal or noninfectious diagnosis.
Unsupervised exposure correction for video

The paper describes an "off-the-shelf" algorithmic solution for unsupervised exposure correction for video. An important feature of the algorithm is accurate processing not only for natural video sequences, but also for edited, rendered or combined content, including content with letter-boxes or pillar-boxes captured from TV broadcasts. The algorithm allows to change degree of exposure correction smoothly for continuous video scenes and to change it promptly on cuts. Solution includes scene change detection, letter-box detection, pillar-box detection, exposure correction adaptation, exposure correction and color correction. Exposure correction adaptation is based on histogram analysis and soft logics inference. Decision rules are based on relative number of entries in the low tones, mid tones and highlights, maximum entries in the low tones and mid tones, number of non-empty histogram entries and width of the middle range of the histogram. All decision rules have physical meaning, which allows to tune parameters easily for display devices of different classes. Exposure correction consists of computation of local average using edge-preserving filtering, applying local tone mapping and post-processing. At the final stage color correction aiming to reduce color distortions is applied.
Comparison of the Nucleotide Sequence at the 5′ End of RNAs from Nine Aphthoviruses, Including Representatives of the Seven Serotypes

The sequence of about 70 nucleotides at the 5′ end of the RNAs of nine different aphthoviruses (foot-and-mouth disease viruses), including representatives of the seven serotypes of the virus, has been determined by partial enzyme digestion of 32P-end-labeled S fragment—that part of the RNA lying to the 5′ side of the poly(C) tract and including the 5′ end of the molecule. The S fragments were prepared from polyadenylated virus-specific RNA extracted from infected cells by digestion with RNase H in the presence of oligo(dG)12-18. The first 27 nucleotides from the 5′ end were highly conserved in all the RNAs. This region was followed by a more variable region of about 15 nucleotides, showing some length and sequence heterogeneity and including potential but probably nonutilized initiation codons. In agreement with previous homology studies, the sequencing results showed that the European serotypes A, O, and C form a group distinct from the SAT serotypes and that the Asia 1 serotype is closely related to the European group. The lengths of the S fragments of two different RNAs were confirmed as containing 360 to 400 nucleotides by gel electrophoresis with reference to nucleotide markers of known size.
The Therapeutic Relationship and Alliance-Building Behaviors : Treatment Implications for Childhood Social Phobia

The importance of alliance in therapy has been well documented. This study explored specific therapist behaviors and their relationship to child perceived alliance and outcome in a randomized controlled trial of a cognitive-behavioral treatment for youth anxiety disorders. Participants included 42 youth (male = 24; female = 18; Caucasian = 37; African American = 4; Hispanic = 1) between the ages of 7 and 13 years who met criteria for a principal anxiety diagnosis. The study examined the sample as a whole, as well as focused specifically on youth diagnosed with social phobia. Videos of the first session of treatment were coded for the presence of 11 therapist behaviors (seven positive and four negative) using the Therapist Alliance Building Behaviors Scale (TABBS). The results indicated that negative-valance therapist behaviors predicted perceived alliance in children who had a principal anxiety diagnosis other than social phobia. Findings suggest that avoiding negative behaviors may have more of an effect on alliance than engaging in positive behaviors with some populations. Future research should continue to identify therapist behaviors that might contribute to or rupture a working alliance in the youth population.
MutS deficiency and activity of the error‐prone DNA polymerase IV are crucial for determining mucA as the main target for mucoid conversion in Pseudomonas aeruginosa

Pseudomonas aeruginosa colonizes the respiratory tract of cystic fibrosis (CF) patients, where mutators along with mucoid variants emerge leading to chronic infection. Mucoid conversion generally involves mutations inactivating the mucA gene. This study correlates the frequency and nature of mucA mutations with the activity of factors determining the mutation rate, such as MutS and polymerase IV (Pol IV). Results show that: (i) the emergence frequency of mucoid variants was higher in isolates arising from mutS populations compared with the wild‐type strain; (ii) in both strains mucoid conversion occurred mainly by mucA mutations; (iii) however, the mutator strain harboured mostly mucA22 (a common allele in CF isolates), while the wild type showed a wider spectrum of mucA mutations with low incidence of mucA22; (iv) disruption of dinB in the wild‐type and mutS strains decreased drastically the emergence frequency of mucoid variants; (v) furthermore, the incidence of mucA mutations diminished in the mutS dinB double mutant strain which consisted only in mucA22; (vi) finally, the mucoid isolates obtained from the dinB strain showed an unexpected absence of mucA mutations. Taken together results demonstrate the implication of both MutS and Pol IV in determining mucA as the main target for conversion to mucoidy.
Anti‐inflammatory action of Cudrania tricuspidata on spleen cell and T lymphocyte proliferation

This study examined whether an extract of Cudrania tricuspidata shows anti‐proliferative effects in anti‐CD3/CD28‐mediated spleen and CD4+CD25− T cells and decreases the production of the pro‐inflammatory cytokines interleukin‐2 (IL‐2) and interferon‐γ (IFN‐γ) in anti‐CD3/CD28‐mediated CD4+CD25− T cells. The proliferation of anti‐CD3/CD28‐mediated spleen cells and CD4+CD25− T cells was effectively suppressed by C. tricuspidata. This extract, however, did not show cytotoxicity in spleen cells under conditions where the antigen was not stimulated using CCK‐8 analysis. C. tricuspidata also decreased the production of the pro‐inflammatory cytokines IL‐2 and IFN‐γ by selective inhibition of this extract on proliferating cells in anti‐CD3/CD28‐mediated CD4+CD25− T cells. These results suggest that C. tricuspidata may be useful in the treatment of autoimmune diseases and organ transplantation through the inhibitory action of T cells in inflammation.
EXPERIMENTAL EVALUATION OF DIFFERENT FILLERS IN DENTAL COMPOSITES IN TERMS OF MECHANICAL PROPERTIES

The aim of this study was to evaluate in vitro the influence of nano-sized filler particles and agglomerates of nano particles (nano cluster) in resin based dental composite material. Four commercially available resins based dental composites-Filtek Z250, Filtek Supreme, Filtek Z100 (3M ESPE, St Paul, MN, USA), Heliomolor (Ivoclar Vivadent, Schaon, Liechtenstein) containing different filler particle type and morphologies were investigated. The compressive strength, compressive modulus, flexural modulus and flexural strength of these composites were evaluated. The nano clusters provided a distinct reinforcing mechanism compared with the microhybrid, microfill or nanohybrid resin based composites resulting in significant improvement to the strength and reliability.
Improving Purchase Behavior Prediction with Most Popular Items

Purchase behavior prediction is one of the most important issues to promote both e-commerce companies’ sales and the consumers’ satisfaction. The prediction usually uses features based on the statistics of items. This kind of features can lead to the loss of detailed information of items. While all items are included, a large number of features has the negative impact on the efficiency of learning the predictive model. In this study, we propose to use the most popular items for improving the prediction. Experiments on the real-world dataset have demonstrated the effectiveness and the efficiency of our proposed method. We also analyze the reason for the performance of the most popular items. In addition, our work also reveals if interactions among most popular items are taken into account, the further significant improvement can be achieved. One possible explanation is that online retailers usually use a variety of sales promotion methods and the interactions can help to predict the purchase behavior. key words: recommender system, behavior analysis, prediction, ecommerce, session