Miracle-dz/UniFAR-FTUs huggingface dataset:
Large Time Behavior of Boosting Algorithms for Regression and Classification

1 2 We exploit analogies between regression and classiication to study certain properties of boosting algorithms. A geometric concept called the angular span is deened and related to analogs of the VC dimension and the pseudo dimension of the regression and classiication systems, and to the assumption of the weak learner. The exponential convergence rates of boosting algorithms are shown to be bounded below by essentially the angular spans. Suucient conditions for nonzero angular span are given and validated for a number of regression and classiication systems. For the case of xed or discrete random predictors, we provide bounds for the predictive mean square errors or the misclassiication probabilities that are tight in the large time limit of boosting, which are shown to be related to the noisy level of the data. 2 AMS 1991 subject classiications. Primary 62G99; secondary 68T99.
Tumor-Targeted Human T Cells Expressing CD28-Based Chimeric Antigen Receptors Circumvent CTLA-4 Inhibition

Adoptive T cell therapy represents a promising treatment for cancer. Human T cells engineered to express a chimeric antigen receptor (CAR) recognize and kill tumor cells in a MHC-unrestricted manner and persist in vivo when the CAR includes a CD28 costimulatory domain. However, the intensity of the CAR-mediated CD28 activation signal and its regulation by the CTLA-4 checkpoint are unknown. We investigated whether T cells expressing an anti-CD19, CD3 zeta and CD28-based CAR (19-28z) displayed the same proliferation and anti-tumor abilities than T cells expressing a CD3 zeta-based CAR (19z1) costimulated through the CD80/CD28, ligand/receptor pathway. Repeated in vitro antigen-specific stimulations indicated that 19-28z+ T cells secreted higher levels of Th1 cytokines and showed enhanced proliferation compared to those of 19z1+ or 19z1-CD80+ T cells. In an aggressive pre-B cell leukemia model, mice treated with 19-28z+ T cells had 10-fold reduced tumor progression compared to those treated with 19z1+ or 19z1-CD80+ T cells. shRNA-mediated CTLA-4 down-regulation in 19z1-CD80+ T cells significantly increased their in vivo expansion and anti-tumor properties, but had no effect in 19-28z+ T cells. Our results establish that CTLA-4 down-regulation may benefit human adoptive T cell therapy and demonstrate that CAR design can elude negative checkpoints to better sustain T cell function.
Multilevel maximum entropy threshold selection based on quantum particle swarm optimization

The maximum entropy threshold has been proven as an efficient method in image segmentation for bilevel thresholding. However, this method becomes very time-consuming when extended to multilevel threshold problem. To solve the problem, a multilevel maximum entropy threshold method based on quantum particle swarm optimization is proposed. The experimental results demonstrate the success of the proposed image thresholding method, as compared with ES-Kapur method and GA-Kapur method.
Extraction of visual information in basketball broadcasting video for event segmentation system

Video analysis is an essential process to segment and summarize sports videos automatically. In this paper, we propose fast and simple computer vision algorithms which can be employed to an event segmentation system for basketball broadcasting videos. In our approach, camera panning is estimated by the optical flow estimation and flow segmentation algorithms. For recognizing shot classes and clock digits, Convolutional Neural Network (CNN) is used. By the experiment, it is observed that our algorithms operate in real time and are accurate to be adapted to the event segmentation system.
Optimal wireless power transfer and harvested power allocation for diffusion LMS in wireless sensor networks

This paper investigates the use of wireless power transfer (WPT) for measurement sensing and information transmission in a wireless sensor network (WSN) performing distributed parameter estimation using an adaptive diffusion least mean-squares (LMS) strategy. We consider a hybrid WSN consisting of common sensor nodes (CNs) and super sensor nodes (SNs) that are capable of WPT. In each diffusion iteration, all nodes sense measurements and exchange parameter estimates with their neighbors. Each SN also transfers wireless power to its neighboring CNs via beamforming. To minimize the steady-state network mean-square-deviation (MSD), we jointly optimize the beamforming parameters for SNs to perform WPT, and the fraction of the harvested power allocated by each CN to measurement sensing and information transmission. We show that the problem is primal decomposable, and propose a distributed subgradient-based algorithm to find the optimal solutions in an iterative manner. Simulation results suggest that compared to the conventional case where there is no WPT, the network MSD is reduced by up to approximately 10 dB, because of lower sensing noise and higher information transmission power due to the additional harvested power at the CNs.
Regaining normalcy after war: ICT-enabled ‘transition resilience’ in veterans and refugees

Our research focuses broadly on the Information and Communication Technology (ICT) enabled practices that people develop in response to disruption—an emergent phenomenon dubbed transition resilience. In our larger project, we seek to understand the ICT choices that people make, how ICT use changes, and how ICTs enable people to create a new sense of normalcy when undergoing periods of chronic disruption. Here, we explore the transition experiences of United States (US) veterans reintegrating into civil society and refugees integrating into the US social system. Veterans experience multiple transitions at once and institutional support to help them regain normalcy is often poor. Refugees also undergo multiple transitions when integrating into a new civil society. Both groups face unique identity crises in their respective transitions. Our work contributes to the development of new ICT-enabled tools to help people recover and regain normalcy in their lives.
Standardization and Scoring of the Body Surface Area (BSA) Formulas for Calculation of the Doses of Anticancer Agents for Cancer Patients from the North-Western Nigeria

Background: Allometric scaling is an empirical examination of the relationship between the pharmacokinetic parameters and body size. Because of the importance of body surface area formulas for calculation of anticancer agents, there is need to standardize and score all the existing body surface area formulas with a view to obtaining the best and most efficient formula that can be adopted for use by our hospitals. Methods: A total of 33 (10.3%) out of 319 presented to the Haematology Department of Usmanu Danfodiyo University Sokoto, Nigeria were diagnosed of Leukaemia and lymphoma. Cyclophosphamide, daunorubicin, vincristine, adriamyin and chlorambucil were used for the treatments. Eleven (11) of the affected 33 patients were randomly selected for calculation of their body surface areas using the formulas of DuBois, Boyd, Gehan and George, Haycock et al., Monsteller, Wang et al., Takashira and Fujimoto. The mean of the results obtained from each formula and for each individual was calculated and compared with all the results provided by the respective formulas and all the formulas scored. Results: Wang et al. recorded the highest score 21 (21.2%) followed by DuBois 20(20.2%), this paper 18 (18.2%), Monsteller 18 (18.2%), Haycock et al. 14 (14.2%), Boyd 13 (13.1%), Gehan and George 13(13.1%), Takashira 4 (4.0%) and Fujimoto 3 (3.0%). Conclusion: Wang et al. gives moderate effective anticancer doses and it is therefore recommended for the patients. It provides neither moderate doses of anticancer agents that may neither cause increased toxicity signs nor high risk of cancer remission.
Differential Regulation of microRNAs by p53 Revealed by Massively Parallel Sequencing: miR-34a is a p53 Target That Induces Apoptosis and G1-arrest

In a genome‑wide screen for microRNAs regulated by the transcription factor encoded by the p53 tumor suppressor gene we found that after p53‑activation the abundance of thirty-four miRNAs was significantly increased, whereas sixteen miRNAs were suppressed. The induction of miR‑34a was most pronounced among all differential regulations. Also expression of the primary miR‑34a transcript was induced after p53 activation and by DNA damage in a p53‑dependent manner. p53 occupied an evolutionarily conserved binding site proximal to the first non-coding exon of miR‑34a. Ectopic miR‑34a induced apoptosis and a cell cycle arrest in the G1-phase, thereby suppressing tumor cell proliferation. Other p53‑induced miRNAs identified here may also have tumor suppressive potential as they are known to suppress the anti‑apoptotic factor Bcl2 (miR‑15a/16) and the oncogenes RAS and HMGA2 (let‑7a). Our results for the first time directly integrate the regulation of miRNA expression into the transcriptional network regulated by p53. siRNAs corresponding to p53‑induced miRNAs may have potential as cancer therapeutic agents as RNA interference based therapies are currently emerging.
Frontiers in Computational Neuroscience

motors (Bath et al., 2005), nanoscale DNA shapes and patterns (Rothemund, 2006), fi xed-width cellular automata (Fujibayashi et al., 2008), and many others. Tile systems are one of the most important mathematical models of self-assembly systems (see e.g., Adleman, 2000; Rothemund et al., 2004). A Wang tile is an oriented unit square with each edge covered by a specifi c " glue ". Tiles are placed on the two-dimensional plane, and two adjacent tiles stick together if and only if they have the same glue on their abutting edges. Wang tiles, fi rst proposed by Wang (1961), have been extensively studied before fi nding their natural applications to self-assembly. More recently, Wang tiles and some of their variants, e. , have been widely used as models for self-assembly and used to design and analyze successful practical experiments (see e.g., Rothemund et al., 2004; Barish et al., 2005). Although quite intuitive, the idea of glues placed on the edges of a tile is not always natural for simulating the interactions occurring in some real systems. For example, when considering protein self-assembly, the shape of a protein is essential in determining its function and its interactions with other proteins. Tiles of various shapes had been previously designed and studied in the literature for specifi c purposes. For example, Robinson (1971) designed six polygonal tiles (squares with notched edges and corners) in the context of solving the problem of minimization of the number of tiles that allowed only aperiodic tilings of the plane. In this paper, we design geometrical tiles, i.e., square tiles with protrusions on their edges, for the purpose of simplifying neighborhood relationships in tiling systems. Our main goal is to simulate any tiled path (" zipper ") that uses tiles with an arbitrarily complex neighborhood, by a " ribbon " of new geometrical
Assessing Preschool Children’s Knowledge of Compounds from a Logico- Semantic Perspective

Research in First Language Acquisition investigates three broad questions: What do children know about language? When does this knowledge emerge? How is children’s knowledge of language different from adults’ knowledge of language? This study adds to previous research in FLA by investigating the interaction between logic and meaning in child language. This study examines preschool children’s comprehension of the logical relation between a compound and its head noun in comparison to adult’s logico-semantic interpretation of compounds.
The Network of Brodmanns Area 22 in Lexico-semantic Processing: A Pooling-data Connectivity Study

Background and Objective:Modern neuroimaging has demonstrated that cognitive functions are based in networks of interconnected modules. The purpose of this paper was to analyze the connectivity of Brodmann's area (BA) 22 in lexico-semantic tasks. MethodsA connectivity fMRI co-activation study was performed by pooling data of lexico-semantic tasks in which BA22 (core of Wernicke's area) was reported. 283 subjects reported in 21 experiments were analyzed. Analysis of Likelihood Estimates of pooled data was utilized to generate the connectivity map; thresholds at p< 0.01 were corrected for multiple comparisons with false discovery rate. Resulting images were co-registered into MNI standard space.Results:network consisting of 13 clusters of activation was obtained. Main clusters were located in the left posterior temporal and left inferior frontal gyrus; in addition to these canonical areas, left insula, pre-supplementary motor area, left BA37, primary auditory areas and left occipital lobe were also involved. Conclusions: BA22-related networks involved in lexico-semantics processing were demonstrated utilizing a pooling-data connectivity study. Significance, interpretation and limitations of the results are discussed.
Log-Based Chat Room Monitoring Using Text Categorization: A Comparative Study

The Internet has been utilized in several real life aspects such as online searching, distance learning, and chatting. On the other hand, the Internet has been misused in communication of crime related matters. Monitoring of such communication would aid in crime detection or even crime prevention. This paper presents a text categorization approach for automatic monitoring of chat conversations since the current monitoring techniques are basically manual, which is tedious, costly, and time consuming. We present the results of a cross method comparison between the Naive Bayes, the K-nearest neighbor, and the Support Vector Machine classifiers. Our objective is to determine the most suitable method for the data of chat conversations. Our results showed that the chat room monitoring task can be efficiently automated using the appropriate text categorization method.
Feature based opinion mining of online free format customer reviews using frequency distribution and Bayesian statistics

Nowadays, a large number of websites allow users to post reviews about products they bought. There are thousands of reviews of customers related to one product. So it is difficult for the manufacturers and also for the customers to have an idea about the product from these large reviews. In this paper we aim to summarize the customer reviews in factual form as done using two statistical techniques that Bayesian statistics and frequency distribution. The proposed system reads the reviews word by word and finally it finds out the summarized result in terms of frequency and probability of opinions. Bayesian probability is the most current and useful for accurate results and true predictions. Frequency results are in graphical form, the use by a new customer can easily decision to buy the product displayed. Frequency based results can be easily understood by all consumer and the results of Bayesian probability are used to verify the results of frequency. In our experimental results, it proves that proposed statistical techniques are highly effective.
Monotonic filter for hierarchical translation models

The model size and decoding time are known issues in statistical machine translation. Especially, monotonic words order of language pairs makes the size of hierarchical models huge. Considering this fact, the rule extraction method of phrase-boundary model was changed to extract less number of rules. This paper proposes this rule extraction method as a general filter for hierarchical models. Named as monotonic filter, this filter reduces the extracted rules from phrase pairs decomposable to monotonic aligned subphrases. We apply the monotonic filter on the hierarchical phrase-based, SAMT and phrase-boundary models. Our experiments are performed in translations from Persian, German and French to English as the source and target languages with low, medium and high monotonic word order respectively. The reduction amount of the monotonic filter for the model size and decoding time is up to about 70% and 80% respectively, in most cases with no tangible impact on the translation quality.
The Viability of Pay What You Want Pricing

Authors are encouraged to submit new papers to INFORMS journals by means of a style file template, which includes the journal title. However, use of a template does not certify that the paper has been accepted for publication in the named journal. INFORMS journal templates are for the exclusive purpose of submitting to an INFORMS journal and should not be used to distribute the papers in print or online or to submit the papers to another publication.
Secrecy rate of channel-aware randomized secure transmission schemes in multicarrier systems

In this paper, we study channel-aware (CA) randomization for secure transmissions in a multicarrier system based on partial channel state information (CSI). In order to see the performance gain by CA randomization, we consider the secrecy rate and show that i) a positive secrecy rate can be obtained even if the channel to an adversary is stochastically more capable than the channel to a legitimate receiver and ii) the normalized secrecy rate can increase with the number of subcarriers. More importantly, it is shown that there is an additional gain due to CA randomization that allows a growth rate of the normalized secrecy faster than linear.
The Perceptions of Participation in a Mobile Collaborative Learning among Pre-Service Teachers.

This study uses Facebook as a platform and arranges certain learning tasks to identify the feasibility of mobile collaborative learning for pre-service teachers. The pre-service teachers’ sense of community and perceptions of collaborative learning are investigated. A total of 153 pre-service teachers volunteered to participate in an Intern Mobile Collaborative Learning Facebook Group from July 2015 to October 2015. During participating in the Facebook Group, pre-service teachers were required to achieve various tasks regarding collaborative learning. A questionnaire, consisting of three sections, frequency, sense of community, and perceptions of learning and perceptions of collaborative learning, was developed and validated. All participants were required to fill in the questionnaire at the last week of the project’s schedule. This study concludes that high browsing frequency on Facebook Group could positively facilitate the sense of community and perceptions of collaborative learning among pre-service teachers; while high frequency of posting and responding to messages on Facebook Group merely promotes perceptions of collaborative learning. The conclusion identifies that assigned tasks like posting and responding to messages regarding school field-based experiences are necessary in mobile collaborative learning among pre-service teachers.
Master Equations for Perturbations of Generalised Static Black Holes with Charge in Higher Dimensions

We extend the formulation for perturbations of maximally symmetric black holes in higher dimensions developed by the present authors in a previous paper to a charged black hole background whose horizon is described by an Einstein manifold. For charged black holes, perturbations of electromagnetic fields are coupled to the vector and scalar modes of metric perturbations non-trivially. We show that by taking appropriate combinations of gauge-invariant variables for these perturbations, the perturbation equations for the Einstein-Maxwell system are reduced to two decoupled second-order wave equations describing the behaviour of the electromagnetic mode and the gravitational mode, for any value of the cosmological constant. These wave equations are transformed into Schrodinger-type ODEs through a Fourier transformation with respect to time. Using these equations, we investigate the stability of generalised black holes with charge. We also give explicit expressions for the source terms of these master equations with application to the emission problem of gravitational waves in mind.
Multitasking SecB chaperones in bacteria

Protein export in bacteria is facilitated by the canonical SecB chaperone, which binds to unfolded precursor proteins, maintains them in a translocation competent state and specifically cooperates with the translocase motor SecA to ensure their proper targeting to the Sec translocon at the cytoplasmic membrane. Besides its key contribution to the Sec pathway, SecB chaperone tasking is critical for the secretion of the Sec-independent heme-binding protein HasA and actively contributes to the cellular network of chaperones that control general proteostasis in Escherichia coli, as judged by the significant interplay found between SecB and the trigger factor, DnaK and GroEL chaperones. Although SecB is mainly a proteobacterial chaperone associated with the presence of an outer membrane and outer membrane proteins, secB-like genes are also found in Gram-positive bacteria as well as in certain phages and plasmids, thus suggesting alternative functions. In addition, a SecB-like protein is also present in the major human pathogen Mycobacterium tuberculosis where it specifically controls a stress-responsive toxin–antitoxin system. This review focuses on such very diverse chaperone functions of SecB, both in E. coli and in other unrelated bacteria.
Fractional-order PID controller tuning based on genetic algorithm

Because the fractional-order systems model is complex and the fractional-order controller requires more tuning parameters than that of integer-order controller, the tuning parameters method of fractional-order PI<sup>λ</sup>D<sup>μ</sup> controller is difficult to obtain. In order to improve the accuracy of fractional-order PI<sup>λ</sup>D<sup>μ</sup> controller, the character and the designing method of fractional-order PID controller is analyzed in this paper, and the genetic algorithm is introduced to the design of fractional-order <sup>λ</sup>D<sup>μ</sup> controller. By using the genetic algorithm to optimize the corresponding parameters, a better PID controller which has a superior is obtained, the error of fractional-order PID controller is avoided and the tuning efficiency is improved. The results of simulation show that the controlling effect of the fractional-order <sup>λ</sup>D<sup>μ</sup> controller is better than that of the integer-order PID controller.
Racial differences in diabetes-related psychosocial factors and glycemic control in patients with type 2 diabetes

Background: We examined whether diabetes-related psychosocial factors differ between African American and white patients with type 2 diabetes. We also tested whether racial differences in glycemic control are independent of such factors. Methods: Baseline glycosylated hemoglobin (HbA1c) and survey measures from 79 African American and 203 white adult participants in a diabetes self-management clinical trial were analyzed. Results: Several psychosocial characteristics varied by race. Perceived interference of diabetes with daily life, perceived diabetes severity, and diabetes-related emotional distress were higher for African Americans than for whites, as were access to illness-management resources and social support. Mean HbA1c levels were higher among African Americans than whites (8.14 vs 7.40, beta = 0.17). This difference persisted after adjusting for demographic, clinical, and diabetes-related psychosocial characteristics that differed by race (beta = 0.18). Less access to illness-management resources (beta = −0.25) and greater perceived severity of diabetes (beta = 0.21) also predicted higher HbA1c. Discussion: Although racial differences in diabetes-related psychosocial factors were observed, African Americans continued to have poorer glycemic control than whites even after such differences were taken into account. Interventions that target psychosocial factors related to diabetes management, particularly illness-management resources, may be a promising way to improve glycemic control for all patients.