Miracle-dz/UniFAR-FTUs huggingface dataset:
T-Cell Response to Human Papillomavirus Type 58 L1, E6, and E7 Peptides in Women with Cleared Infection, Cervical Intraepithelial Neoplasia, or Invasive Cancer

ABSTRACT Human papillomavirus type 58 (HPV-58) exists in a relatively high prevalence in certain parts of the world, including East Asia. This study examined the T-cell response to HPV-58 L1, E6, and E7 peptides among women with cleared infection, cervical intraepithelial neoplasia grade 2 (CIN2) or CIN3, or invasive cervical cancer (ICC). Peptides found to be reactive in the in vitro peptide binding assay or mouse-stimulating study were tested with a gamma interferon (IFN-γ) enzyme-linked immunospot (ELISPOT) assay to detect peptide-specific responses from the peripheral blood mononuclear cells (PBMC) collected from 91 HPV-58-infected women (32 with cleared infection, 16 CIN2, 15 CIN3, and 28 ICC). Four HLA-A11-restricted HPV-58 L1 peptides, located at amino acid positions 296 to 304, 327 to 335, 101 to 109, and 469 to 477, showed positive IFN-γ ELISPOT results and were mainly from women with cleared infection. Two HLA-A11-restricted E6 peptides (amino acid positions 64 to 72 and 94 to 102) and three HLA-A11-restricted E7 peptides (amino acid positions 78 to 86, 74 to 82, and 88 to 96) showed a positive response. A response to E6 and E7 peptides was mainly observed from subjects with CIN2 or above. One HLA-A2-restricted E6 peptide, located at amino acid position 99 to 107, elicited a positive response in two CIN2 subjects. One HLA-A24-restricted L1 peptide, located at amino acid position 468 to 476, also elicited a positive response in two CIN2 subjects. In summary, this study has identified a few immunogenic epitopes for HPV-58 E6 and E7 proteins. It is worthwhile to further investigate whether responses to these epitopes have a role in clearing an established cervical lesion.
Secure and optimized data storage for IoT through cloud framework

Internet of Things (IoT) is the future. With increasing popularity of internet, soon internet in routine devices will be a common practice by people. Hence we are writing this paper to encourage IoT accomplishment using cloud computing features with it. Basic setback of IoT is management of the huge quantity of data. In this paper, we have suggested a framework with several data compression techniques to store this large amount of data on cloud acquiring lesser space and using AES encryption techniques we have also improved the security of this data. Framework also shows the interaction of data with reporting and analytic tools through cloud. At the end, we have concluded our paper with some of the future scopes and possible enhancements of our ideas.
Dual-threshold voltage assignment with transistor sizing for low power CMOS circuits

We demonstrate a novel algorithm for assigning the threshold voltage to the gates in a digital random logic CMOS circuit for a dual-threshold voltage process. The tradeoff between static and dynamic power consumption has been explored. When used along with device sizing and supply voltage reduction techniques for low power, the proposed algorithm can reduce the total power dissipation of the circuits by as much as 50%.
Efficacy of the Check & Connect Mentoring Program for At-Risk General Education High School Students

ABSTRACT Although graduation rates are rising, the high school dropout problem remains a national crisis, and evidence-based information about interventions for at-risk students is critically needed. Prior research shows that Check & Connect, an individualized mentoring program, has positive effects on school persistence and progression for students with disabilities. This study examined the efficacy of Check & Connect with general education students who showed early warning signs of risk for dropping out of high school in a large urban district. The sample included 553 students with the lowest predicted probabilities of on-time graduation based on attendance, behavior, and course performance in Grades 8 and 9. Students were randomly assigned to receive a Check & Connect mentor for three years, starting in the summer after Grade 9, or not. Findings suggest the program was implemented with fidelity, except with students who left district schools. Check & Connect did not have any statistically significant impacts on measures of engagement, academic progress, the likelihood of dropping out, or graduation. These results are discussed in the context of other literature on mentoring and dropout prevention.
Divide-and-conquer learning and modular perceptron networks

A novel modular perceptron network (MPN) and divide-and-conquer learning (DCL) schemes for the design of modular neural networks are proposed. When a training process in a multilayer perceptron falls into a local minimum or stalls in a flat region, the proposed DCL scheme is applied to divide the current training data region into two easier to be learned regions. The learning process continues when a self-growing perceptron network and its initial weight estimation are constructed for one of the newly partitioned regions. Another partitioned region will resume the training process on the original perceptron network. Data region partitioning, weight estimating and learning are iteratively repeated until all the training data are completely learned by the MPN. We evaluated and compared the proposed MPN with several representative neural networks on the two-spirals problem and real-world dataset. The MPN achieved better weight learning performance by requiring much less data presentations during the network training phases, and better generalization performance, and less processing time during the retrieving phase.
STEPS: Predicting place attributes via spatio-temporal analysis

In recent years, a vast amount of research has been conducted on learning people's interests from their actions. Yet their collective actions also allow us to learn something about the world, in particular, infer attributes of places people visit or interact with. Imagine classifying whether a hotel has a gym or a swimming pool, or whether a restaurant has a romantic atmosphere without ever asking its patrons. Algorithms we present can do just that. Many web applications rely on knowing attributes of places, for instance, whether a particular restaurant has WiFi or offers outdoor seating. Such data can be used to support a range of user experiences, from explicit query-driven search to personalized place recommendations. However, obtaining these attributes is generally difficult, with existing approaches relying on crowdsourcing or parsing online reviews, both of which are noisy, biased, and have limited coverage. Here we present a novel approach to classifying place attributes, which learns from patrons' visit patterns based on anonymous observational data. Our method, STEPS, learns from aggregated sequences of place visits. For example, if many people visit the restaurant on a Saturday evening, coming from a luxury hotel or theater, and stay for a long time, then this restaurant is more likely to have a romantic atmosphere. On the other hand, if most people visit the restaurant on weekdays, coming from work or a grocery store, then the restaurant is less likely to be romantic. We show that such transition features are highly predictive of place attributes. In an extensive empirical evaluation, STEPS nearly doubled the coverage of a state of the art approach thanks to learning from observational location data, which allowed our method to reason about many more places.
Optimized Maximum Power Point Tracker for Fast-Changing Environmental Conditions

This paper presents a high-performance maximum power point tracker (MPPT) optimized for fast cloudy conditions, e.g., rapidly changing irradiation on the photovoltaic panels. The rapidly changing conditions are tracked by an optimized hill-climbing MPPT method called dP-P&O. This algorithm separates the effects of the irradiation change from the effect of the tracker's perturbation and uses this information to optimize the tracking according to the irradiation change. The knowledge of the direction of the irradiation change enables the MPPT to use different optimized tracking schemes for the different cases of increasing, decreasing, or steady irradiance. When the irradiance is changing rapidly this strategy leads to faster and better tracking, while in steady-state conditions it leads to lower oscillations around the MPP. The simulations and experimental results show that the proposed dP-P&O MPPT provides a quick and accurate tracking even in very fast changing environmental conditions.
Effects of grasses on sapling establishment and the role of transplanted saplings on the light environment of pastures: implications for tropical forest restoration

Question: Does the presence of grasses affect the establishment (survival and growth) of treesaplingsin an abandoned tropical pasture, and what isthe potential of established saplings to modify pasture microenvironmental conditions, particularly light incidence? Location: Abandoned cattle pasture, in the humid tropics of SE Mexico (18°25′ –18°45′ N, 95°00′–95°18′ W). Methods: The establishment of four native fast-growing tree species in a tropical abandoned pasture was evaluated. Saplings of Cecropia obtusifolia, Hampea nutricia, Omphalea oleifera and Erythrina folkersii were transplanted using a split-plot design. Plant survival and growth were evaluated over 12 mo under two experimental treatments: presence and absence of grasses. Light incidence at ground level was used to evaluate microclimate conditions under the grass matrix, compared to light incidence under saplings established in the pasture. Results: Saplings had high survival (49–88%) regardless of the presence of grasses. In the presence of grasses, growth of surviving saplings either increased or was not impacted, and in only one out of eight comparisons did grasses negatively affect growth. The impact of saplings on light incidence in abandoned pastures depended on sapling species architecture: species with large total leaf area and canopy area (H. nutricia and E. folkersii )s ignif icantly reduced light incidence (12–29% of total incidence), while narrow-canopy species (C. obtusifolia and O. oleifera) generated less intense shade (37–89% of total incidence). Conclusions: Grasses did not seem to represent a crucial limiting factor in sapling establishment of fast-growing native species in the short term. In addition, shading by recruited saplings of some native species could be important to outcompete grasses in the future, as well as for ‘facilitating’ regeneration of more shade-tolerant species. Transplantation of fast-growing native saplings into abandonedpastures,even without manipulation of the grasses,could bea useful practice for landscape-scale restoration programmes in tropical areas. Evaluation of the longer-term consequences (beyond the 1-yr span of this study) warrants further research.
Distribution and ontogeny of gastrin- and serotonin-immunoreactive cells in the proventriculus of developing chick, Gallus gallus domestica

The ontogeny and distribution of gastrin- and serotonin-immunoreactive (IR) cell in the proventriculus of chicks (Gallus gallus domestica, n = 60) in different growth periods was examined immunohistochemically using antisera specific to gastrin and serotonin. Gastrin and serotonin-IR cells were detected in chick proventriculus. Gastrin-IR cells were first evident after 12 days of incubation in lamina epithelialis and compound glands, while serotonin-IR cells were observed only in compound glands at that same time. Gastrin-IR and serotonin-IR cells increased in frequency on incubation day 14 and 16, respectively. Towards the end of incubation, gastrin- and serotonin-IR cell numbers decreased. In adult chicken, both IR cells were present but not lower numbers. The observations demonstrate the presence of gastrin- and serotonin-IR cells in the proventriculus of developing chicks in temporally changing frequencies.
Population ageing policy reforms and endogenous growth in Japan: a computable overlapping generations approach

We have developed a multi-period computable endogenous growth overlapping generations model generated by the accumulation of human capital. To study whether ageing itself and policy reform that aims to cope with aging make any quantitative impact through human capital formation on the Japanese economy, we simulate two policy change scenarios and compare the results of those with endogenous growth to those with exogenous growth. Three main results are obtained: (1) the human capital investment is important to assure sustained positive economic growth; (2) policy changes, pension reform, and fiscal consolidation promote human capital accumulation and thus boost economic growth; and (3) the traditional exogenous growth OLG model underestimates the effect of policy reform, comparing the endogenous growth of the OLG model. The robustness of these results is guaranteed from the sensitivity tests. JEL classification : C62; C63; C68; E27; E66; J11; J24; O41; O53;
Trust the Police? Self-Selection of Motivated Agents into the German Police Force

We conduct experimental games with police applicants in Germany to investigate whether intrinsically motivated agents self-select into this type of public service. Our focus is on trustworthiness and the willingness to enforce norms of cooperation as key dimensions of intrinsic motivation in the police context. We find that police applicants are more trustworthy than non-applicants, i.e., they return higher shares as second-movers in a trust game. Furthermore, they invest more in rewards and punishment when they can enforce cooperation as a third party. Our results provide clear evidence for self-selection of motivated agents into the German police force, documenting an important mechanism that influences the match between jobs and agents in public service. (JEL C91, D73, J41, J45)
EFFICIENT SEMIPARAMETRIC SEEMINGLY UNRELATED QUANTILE REGRESSION ESTIMATION

We propose an efficient semiparametric estimator for the coefficients of a multivariate linear regression model—with a conditional quantile restriction for each equation—in which the conditional distributions of errors given regressors are unknown. The procedure can be used to estimate multiple conditional quantiles of the same regression relationship. The proposed estimator is asymptotically as efficient as if the true optimal instruments were known. Simulation results suggest that the estimation procedure works well in practice and dominates an equation-by-equation efficiency correction if the errors are dependent conditional on the regressors.
Color Sommelier: Interactive Color Recommendation System Based on Community-Generated Color Palettes

We present Color Sommelier, an interactive color recommendation system based on community-generated color palettes that helps users to choose harmonious colors on the fly. We used an item-based collaborative filtering technique with Adobe Color CC palettes in order to take advantage of their ratings that reflect the general public? s color harmony preferences. Every time a user chooses a color(s), Color Sommelier calculates how harmonious each of the remaining colors is with the chosen color(s). This interactive recommendation enables users to choose colors iteratively until they are satisfied. To illustrate the usefulness of the algorithm, we implemented a coloring application with a specially designed color chooser. With the chooser, users can intuitively recognize the harmony score of each color based on its bubble size and use the recommendations at their discretion. The Color Sommelier algorithm is flexible enough to be applicable to any color chooser in any software package and is easy to implement.
A Unique SUMO-2-Interacting Motif within LANA Is Essential for KSHV Latency

Kaposi's sarcoma-associated herpesvirus (KSHV) stabilizes hypoxia-inducible factor α (HIF-1α) during latent infection, and HIF-1α reactivates lytic replication under hypoxic stress. However, the mechanism utilized by KSHV to block lytic reactivation with the accumulation of HIF-1α in latency remains unclear. Here, we report that LANA encoded by KSHV contains a unique SUMO-interacting motif (LANASIM) which is specific for interaction with SUMO-2 and facilitates LANA SUMOylation at lysine 1140. Proteomic and co-immunoprecipitation analysis further reveal that the SUMO-2 modified transcription repressor KAP1 is a critical factor recruited by LANASIM. Deletion of LANASIM led to functional loss of both LANA-mediated viral episome maintenance and lytic gene silencing. Moreover, hypoxia reduced KAP1 SUMOylation and resulted in dissociation of both KAP1 and Sin3A repressors from LANASIM-associated complex. Therefore, the LANASIM motif plays an essential role in KSHV latency and is a potential drug target against KSHV-associated cancers.
Downregulation of hTERT: An Important As2O3 Induced Mechanism of Apoptosis in Myelodysplastic Syndrome

Two myelodysplastic syndrome (MDS) celllines, MUTZ-1 and SKM-1 cells, were used to study the effect of arsenic trioxide (As2O3) on hematological malignant cells. As2O3 induced this two cell lines apoptosis via activation of caspase-3/8 and cleavage of poly (ADP-ribose) polymerase (PARP), a DNA repair enzyme. As2O3 reduced NF-κB activity, which was important for inducing MUTZ-1 and SKM-1 cells apoptosis. As2O3 also inhibited the activities of hTERT in MUTZ-1 and SKM-1 cells. Moreover, the NF-κB inhibitor, pyrrolidine dithiocarbamate (PDTC), had no effect on caspase-8 activation, although PDTC did inhibit MUTZ-1 and SKM-1 cells proliferation. Incubation of MUTZ-1 cells with a caspase-8 inhibitor failed to block As2O3-induced inhibition of NF-κB activity. Our findings suggest that As2O3 may induce apoptosis in MUTZ-1 and SKM-1 cells by two independent pathways: first, by activation of caspase-3/8 and PARP; and second, by inhibition of NF-κB activity, which results in downregulation of hTERT expression. We conclude that hTERT and NF-κB are important molecular targets in As2O3-induced apoptosis.
QCD corrections to the electric dipole moment of the neutron in the MSSM

We consider the QCD corrections to the electric dipole moment of the neutron in the Minimal Supersymmetric Standard Model. We provide a master formula for the Wilson coefficients at the low energy scale including for the first time the mixing between the electric and chromoelectric operators and correcting widely used previous LO estimates. We show that, because of the mixing between the electric and chromoelectric operators, the neutralino contribution is always strongly suppressed. We find that, in general, the effect of the QCD corrections is to reduce the amount of CP violation generated at the high scale. We discuss the perturbative uncertainties of the LO computation, which are particularly large for the gluino-mediated contribution. This motivates our Next-to-Leading order analysis. We compute for the first time the order αs corrections to the Wilson coefficients for the gluino contributions, and recompute the two-loop anomalous dimension for the dipole operators. We show that the large LO uncertainty disappears once NLO corrections are taken into account.
Curvature line parametrization from circle patterns

AbstractWe study local and global approximations of smooth nets of curvaturelines and smooth conjugate nets by respective discrete nets (circular nets andplanar quadrilateral nets) with edges of order ǫ. It is shown that choosingthe points of discrete nets on the smooth surface one can obtain the order ǫ 2 approximation globally. Also a simple geometric construction for approximatedetermination of principal directions of smooth surfaces is given. 1 Introduction Discrete conjugate nets, deﬁned as mappings Z 2 −→ R 3 with the condition thateach elementary quadrangle is ﬂat, and discrete nets of curvature lines, deﬁned asdiscrete conjugate nets with additional property of circularity of the four vertices ofevery elementary quadrangle, play an important role in the contemporary discretediﬀerential geometry (see e.g. [2] for a review) and have important applications tocomputer-aided geometric design [12]. This paper is devoted to a carefull study of the order of approximation of discretenets toa given smooth conjugate net orthe net ofcurvature lines on asmooth surfacethat can be achieved. We also present a remarkably simple approximate construction
Association between low-dose folic acid supplementation and blood lipids concentrations in male and female subjects with atherosclerosis risk factors

Background Folic acid (FA) is one of the B complex vitamins. It is thought that FA deficiency promotes atherosclerosis formation in arterial endothelium. FA, acting through reducing homocysteine (Hcy) levels, may contribute to decreased cholesterol (Ch) synthesis. The aim of this study was to analyze the association of low-dose folic acid supplementation with blood lipids concentrations in subjects with atherosclerosis risk factors. Material/Methods The study enrolled 124 Caucasian individuals (60 M, ages 20–39; and 64 F, ages 19–39) with atherosclerosis risk factors (family history of premature ischemic stroke, arterial hypertension, dyslipidemia, overweight and obesity, cigarette smoking, and low level of physical activity). The participants were asked to take FA at a low dose of 0.4 mg/24 h for 12 weeks. Results FA levels increased in females (6.3 vs. 12.5 ng/dL; p=0.001) and males (6.4 vs. 11.4 ng/dL; p=0.001) and Hcy levels decreased (10.6 vs. 8.3 μmol/L; p=0.001 and 11.5 vs. 9.3; p=0.001, respectively). A significant reduction in mean concentration of total cholesterol in females (203.4 vs. 193.1 mg/dL; p=0.001) and in males (209.5 vs. 201.9; p=0.002) was observed. The low-density lipoprotein cholesterol (LDL-C) levels decreased in females and in males (107.4 vs. 99.9 mg/dL; p=0.001 and 121.5 vs. 115.1; p=0.002, respectively). The apoAI concentrations increased in smoking women and in men with BMI ≥25 kg/m2 (p=0.032 and p=0.024, respectively). Conclusions Low-dose FA supplementation has a beneficial effect on blood lipids through decreasing concentrations of total cholesterol and LDL-C and increasing concentrations of apoAI.
Patterning by genetic networks and modular principle

We consider here the morphogenesis (pattern formation) problem for some genetic network models. First, we show that any given spatio-temporal pattern can be generated by a genetic network involving a sufficiently large number of genes. Moreover, patterning process can be performed by an effective algorithm. We also show that Turing’s or Meinhardt’ s type reactiondiffusion models can be approximated by genetic networks. These results exploit the fundamental fact that the genes form functional units and are organised in blocks (modular principle). Due to this modular organisation, the genes always are capable to construct any new patterns and even any time sequences of new patterns from old patterns. Computer simulations illustrate analytical results.
Reliable Yield Prediction with Regression Neural Networks

: This paper performs an extension to conventional regression neural networks (NNs) for replacing the point predictions they produce with prediction intervals that satisfy a required level of confidence. Our approach follows a novel machine learning framework, called Conformal Prediction (CP), for assigning reliable confidence measures to predictions without assuming anything more than that the data are independent and identically distributed (i.i.d.). We evaluate the proposed method on predicting the weekly yield of tomato in a greenhouse, two datasets were used, which consist of environmental variables inside the greenhouse, namely temperature, CO2, vapour pressure deficit (VPD) and radiation, as well as past yield. Greenhouse environment data and crop records were collected from a large scale commercial operation, Wight Salads Group (WSG) in the Isle of Wight, United Kingdom; we use a dataset of more than 60000 record measurements collected over a period of 11 years. Our experimental results show that the prediction intervals produced by our method are both well calibrated and good enough to be useful in practice.