Miracle-dz/UniFAR-FTUs huggingface dataset:
Therapeutic dendritic cell vaccination against human papillomavirus

5 ORIGINAL PAPERS 6 ABBREVIATIONS 8 INTRODUCTION 9 Overview of the immune system 9 T cells 9 Dendritic cells 13 Toll-like receptors 16 The understanding of cancer a historical overview 18 Viruses and cancer 18 Human papillomavirus and cervical disease 19 Risk factors for cervical cancer 23 Prophylactic vaccines 27 Therapeutic cancer vaccines 28 Cholera toxin as an adjuvant 31 AIMS 32 MATERIAL AND METHODS 33 Recombinant HPV16 E7 33 Murine studies 33 Human studies 35 Statistical analyses 38 RESULTS 39 Induction of MHC expression, leukocyte accumulation and chemokine production in the genital tract by TLR ligands 39 Induction of MHC expression, leukocyte accumulation and chemokine production in experimental tumours by TLR ligands 42 CT as a combinational carrier/adjuvant promotes DC vaccination efficiency against an experimental TC-1 tumour in vivo 43 Conjugation of HPV16 E7 to cholera toxin enhances the HPV-specific human T-cell responses to pulsed DCs in vitro 46 IDO expression in CT-treated DCs 49 DISCUSSION 51 CONCLUDING REMARKS 59 POPULÄRVETENSKAPLIG SAMMANFATTNING 60 ACKNOWLEDGEMENTS 61 REFERENCES 63
Double-Sparsity Learning-Based Channel-and-Signal Estimation in Massive MIMO With Generalized Spatial Modulation

In this paper, we study joint antenna activity detection, channel estimation, and multiuser detection for massive multiple-input multiple-output (MIMO) systems with general spatial modulation (GSM). We first establish a double-sparsity massive MIMO model by considering the channel sparsity of the massive MIMO channel and the signal sparsity of GSM. Based on the double-sparsity model, we formulate a blind detection problem. To solve the blind detection problem, we develop message-passing based blind channel-and-signal estimation (BCSE) algorithm. The BCSE algorithm basically follows the affine sparse matrix factorization technique, but with critical modifications to handle the double-sparsity property of the model. We show that the BCSE algorithm significantly outperforms the existing blind and training-based algorithms, and is able to closely approach the genie bounds (with either known channel or known signal). In the BCSE algorithm, short pilots are employed to remove the phase and permutation ambiguities after sparse matrix factorization. To utilize the short pilots more efficiently, we further develop the semi-blind channel-and-signal estimation (SBCSE) algorithm to incorporate the estimation of the phase and permutation ambiguities into the iterative message-passing process. We show that the SBCSE algorithm substantially outperforms the counterpart algorithms including the BCSE algorithm in the short-pilot regime.
AeroVr: Virtual Reality-based Teleoperation with Tactile Feedback for Aerial Manipulation

Drone application for aerial manipulation is tested in such areas as industrial maintenance, supporting the rescuers in emergencies, and e-commerce. Most of such applications require teleoperation. The operator receives visual feedback from the camera installed on a robot arm or drone. As aerial manipulation requires delicate and precise motion of robot arm, the camera data delay, narrow field of view, and blurred image caused by drone dynamics can lead the UAV to crash. The paper focuses on the development of a novel teleoperation system for aerial manipulation using Virtual Reality (VR). The controlled system consists of UAV with a 4- DoF robotic arm and embedded sensors. VR application presents the digital twin of drone and remote environment to the user through a head-mounted display (HMD). The operator controls the position of the robotic arm and gripper with VR trackers worn on the arm and tracking glove with vibrotactile feedback. Control data is translated directly from VR to the real robot in realtime. The experimental results showed a stable and robust teleoperation mediated by the VR scene. The proposed system can considerably improve the quality of aerial manipulations.
Jet angularities in photoproduction at the Electron-Ion Collider

We consider the one-parameter family of jet substructure observables known as angularities using the specific case of inclusive jets arising from photoproduction events at an Electron-Ion Collider (EIC). We perform numerical calculations at next-to-leading logarithmic accuracy within perturbative QCD and compare our results to PYTHIA 6 predictions. Overall, we find good agreement and conclude that jet substructure observables are feasible at the EIC despite the relatively low jet transverse momentum and particle multiplicities. We investigate the size of subleading power corrections relevant at low energies within the Monte Carlo setup. In order to establish the validity of the Monte Carlo tune, we also perform comparisons to jet shape data at HERA. We further discuss detector requirements necessary for angularity measurements at an EIC, focusing on hadron calorimeter energy and spatial resolutions. Possible applications of precision jet substructure measurements at the EIC include the tuning of Monte Carlo event generators, the extraction of nonperturbative parameters and studies of cold nuclear matter effects.
Career Decision-making Self-Efficacy of Higher Education Students in Tanzania: Does Age, Gender, and Year of Study Matter?

This article presents the findings of study that deployed a cross-sectional survey design to examine a perceived self-efficacy in career decision-making of undergraduate students in Tanzania. Specifically, the study examined the extent to which age, gender, and year of study influence self-efficacy in career decision-making among students in higher education institutions of Tanzania. The study used a sample of 204 business and engineering undergraduate students randomly drawn from two purposively selected public higher education institutions the University of Dar es Salaam and the University of Dodoma. The results showed that the majority of respondents had high career decision-making self-efficacy in terms of goal selection, occupational information, problem-solving, planning, and self-appraisal. Moreover, with the exception of age, the t-test results revealed significant differences in career self-efficacy between female and male students as well as between first and final year students. The results contribute to a better understanding of the development of career decision-making self-efficacy in relation to the students’ gender, age, and year of study in sub-Saharan Africa. Key words : Perceived career self-efficacy, university students, age, gender, year of study, Tanzania
Eco-e ciency of Electric Vehicles in the United States: A Life-Cycle Assessment based Principal Component Analysis

This research presents an integrated sustainability assessment framework for alternative electric vehicle technologies in the United States. Two methods such as life cycle assessment (LCA) and principal component analysis (PCA) are jointly used for eco-e ciency analysis of battery electric vehicles. Three scenarios are analyzed such as marginal electricity mix, average electricity mix and 100% solar energy. Three environmental (water withdrawal, energy consumption and carbon emission) and one economic (life cycle cost) indicators are combined to obtain the eco-e ciency values for 49 U.S. states. First, the scenarios are compared by applying the ANOVA and Tukey HSD test approaches regarding their environmental and economic indicators values. Then, a comparison is executed based on the eco-e ciency values of states in each scenario separately. The maximum scores of eco-e ciency are related to Idaho, Texas and New Mexico based on marginal electricity mix scenario, average electricity mix scenario and solar energy scenario, respectively. According to the results, solar energy scenario is the cleanest scenario because of the least value of environmental impacts while the marginal electricity mix scenario has the highest economic output. Compared to other two scenarios, solar energy scenario cause an extreme decrease in the amount of carbon emission in all states and also reduces the value of water consumption and energy use considerably in most of the states.
Serratia marcescens B4A chitinase thermostability enhancement by S390I QuikChange site directed mutagenesis

Thermostable chitinases are useful for economical, industrial and biotechnological applications. In this paper we attempted to stabilize chitinase from Serratia marcescens B4A by rational mutagenesis and changing of Ser 390 to Ile. This stabilization was performed through entropic stabilization by reduction of the loop length and also by increasing of the beta chain length. On the other hand, with this replacement, polar uncharged residue changed to non-polar one and increased the hydrophobic interactions, furthermore Isoleucine has branched β-carbon that restricted the backbone conformation more than nonbranched residues. Finally all of these factors lead to entropic stabilization and thermal stabilization. The results exhibited that the optimal temperature and pH for enzyme activity of native chitinase weren’t changed by mutagenesis which showed mutation didn’t effect at original characteristics of enzyme, the Km values of native and mutant chitinase was differed very little that showed the affinity of enzyme toward the substrate and natural flexibility of chitinase didn’t changed by mutation, the Vmax value of mutant chitinase was decreased and pH stability of mutant chitinase was increased briefly but its thermal stability was increased remarkably. Mutation made chitinase tolerated high temperatures to 90°C. In addition its activity was increased at 50°C, 60°C for 120 min and up to 2 hours of incubation period and the mutant chitinase showed a high level of activity at 60°C. These results show that entropic stabilization works well for chitinase and this approach may be generally applicable for stabilization of other proteins.
Vertical Relationships in the Ready-to-Eat Cereal Market in Boston

In this paper we estimate a discrete choice demand model with random coefficients for 37 brands of ready-to-eat cereals (RTECs) at the supermarket chain level in the Boston area. Then assuming a manufacturer Stacklberg model for vertical pricing, we decompose the market channel price-cost margins (PCMs) for individual brands at four supermarket chains. The results shed light on the share of channel profits accruing to individual RTEC manufacturers and retailers. For instance, Stop & Shop, the leading supermarket chain in Boston, gets greater dollar profits than smaller supermarket chains. In spite of this, smaller supermarkets, especially those with urban locations, charge higher prices due in part to higher retailing costs. Finally, the results also show that both manufacturers and retailers dropped their RTEC prices in 1996 under a regulatory threat provoked by a scandal of supra-normal RTEC prices.
Italian Journal of Prevention, Diagnostic and Therapeutic Medicine (IJPDTM)

Ciò ha permesso un’evoluzione della professione e delle competenze, oggi si propone un approccio clinico del perfusionista al bypass cardiopolmonare, strutturato sulle caratteristiche del paziente, questo articolo presenta i risultati in un’analisi comparativa di revisione retrospettiva in un singolo centro di bypass metodologia su misura cardiopolmonare (CPB), in termini di gestione, selezione di metodi e tecniche e materiali rispetto alla tecnica standard.
The Longitudinal Discharge Planning and Treatment Model (LDPTM)

Abstract A longitudinally based discharge planning and treatment model that integrates essential components of other successful approaches (PACT, PACED, and Bridge to Discharge) is described. The development of linkages between the inpatient and community mental health providers during the early stages of hospitalization could improve the continuity of care and establish an aftercare plan rooted in existing community resources. Placing the client's need first will ensure a smoother transition from the structure of the inpatient ward to the community while maintaining continuity of care and reducing potential re-admissions to the hospital. Potential barriers that may prevent the adoption and implementation of such a system are discussed. Belcher and DeForge (2005) in Part 1 provided a review of case management and discharge planning, as well as a critique of case management models. In Part 2, DeForge and Belcher (2005) present and describe the components of the longitudinally based discharge planning and treatment model (LDPTM).
Certifiably Globally Optimal Extrinsic Calibration from Per-Sensor Egomotion

We present a certifiably globally optimal algorithm for determining the extrinsic calibration between two sensors that are capable of producing independent egomotion estimates. This problem has been previously solved using a variety of techniques, including local optimization approaches that have no formal global optimality guarantees. We use a quadratic objective function to formulate calibration as a quadratically constrained quadratic program (QCQP). By leveraging recent advances in the optimization of QCQPs, we are able to use existing semidefinite program (SDP) solvers to obtain a certifiably global optimum via the Lagrangian dual problem. Our problem formulation can be globally optimized by existing general-purpose solvers in less than a second, regardless of the number of measurements available and the noise level. This enables a variety of robotic platforms to rapidly and robustly compute and certify a globally optimal set of calibration parameters without a prior estimate or operator intervention. We compare the performance of our approach with a local solver on extensive simulations and multiple real datasets. Finally, we present necessary observability conditions that connect our approach to recent theoretical results and analytically support the empirical performance of our system.
Machine Intelligence for the Detection of Plant Diseases Using Image Processing

-The economic growth of the country depends upon the quality and quantity of the plant production. The diagnosis of the diseases is needed at an earlier stage before it becomes worse. Proper preventive care will increase the production of fruits and vegetables. Thus, automated recognition of diseases in plant plays a vital role in agricultural yields. Several image processing approaches have been developed for disease diagnosis in a short span. In this work, various machine intelligence techniques include SVM, Back Propagation network, Naïve Bayesian are analyzed and observed and concur Gray Level Co-occurrence Matrix (GLCM) based neural network performs better and gives high accuracy. The experimental results validate that the proposed model achieved a test accuracy is found that to around 93% for alternaria alternate, anthracnose, black spot, bacterial blight, cercospora leaf spot diseases in fruit and leaf.
COGNITIVE ACTIVITY OF STUDENTS UNDER CONDITIONS OF DIGITAL TRANSFORMATION OF LEARNING ENVIRONMENT

Technological changes in science, economics and society lead to social, political and cultural changes. Changes in education, among other things, cause some contradictions: between the emergence of the latest technology, technology and the new generation of means for training, management and scientific research and late response of education managers to the choice, implementation and spread of innovation; between the need to develop a modern educational environment and the conservatism of leaders and pedagogical staff in the period of innovation transformations. Based on the computer-technology platform of modern education, which acquires characteristics of open, there is a transformation of traditional learning environment into the environment of computer-mediate communication. This environment is characterized by use of distributed educational resources and infrastructures to support educational communities of different types. We consider cognitive activity as an element of the overall learning process, which is a targeted, systematically organized, managed externally or students’ individual interaction with the surrounding reality, the result of which is the mastery of scholarly knowledge and work methods at the level of reproduction or creativity. In the process of learning, cognition gets clear form in a special and unique to the person educational and cognitive activity, or learning. The effectiveness of educational and cognitive activity of students in particular is determined by the new paradigm of education of the information society. The entire toolkit is changed, that allow evaluating and controlling educational and cognitive activity. ICT and ICN form new solutions that can influence basic processes in the educational system: formation and development of competencies, recording achievements, learning quality assessment, creating a positive motivation and promoting individual educational and cognitive activities. The article deals with research results of problems of organization of educational and cognitive students’ activity and formation of their competencies in the context of transformational changes in the educational process caused by presentation of new technologies.
Aerosol pH and liquid water content determine when particulate matter is sensitive to ammonia and nitrate availability

Abstract. Nitrogen oxides (NOx) and ammonia (NH3) from anthropogenic and biogenic emissions are central contributors to particulate matter (PM) concentrations worldwide. The response of PM to changes in the emissions of both compounds is typically studied on a case-by-case basis, owing in part to the complex thermodynamic interactions of these aerosol precursors with other PM constituents. Here we present a simple but thermodynamically consistent approach that expresses the chemical domains of sensitivity of aerosol particulate matter to NH3 and HNO3 availability in terms of aerosol pH and liquid water content. From our analysis, four policy-relevant regimes emerge in terms of sensitivity: (i) NH3 sensitive, (ii) HNO3 sensitive, (iii) NH3 and HNO3 sensitive, and (iv) insensitive to NH3 or HNO3. For all regimes, the PM remains sensitive to nonvolatile precursors, such as nonvolatile cations and sulfate. When this framework is applied to ambient measurements or predictions of PM and gaseous precursors, the “chemical regime” of PM sensitivity to NH3 and HNO3 availability is directly determined. The use of these regimes allows for novel insights, and this framework is an important tool to evaluate chemical transport models. With this extended understanding, aerosol pH and associated liquid water content naturally emerge as previously ignored state parameters that drive PM formation.
Supplier integration in the Chinese automotive industry: A multiple case study

The aim of this paper is to identify factors that facilitate and inhibit supplier integration in the context of the Chinese automotive industry. An inductive approach based on grounded theory was chosen as research methodology which comprised data collection through 30 case interviews with automotive companies in China. The results indicate that buyer-side leadership is an important antecedent for building motivation, trust and commitment among suppliers and for shaping their mindsets. This in turn facilitates strategic alignment and enables suppliers to build collaborative capabilities. Collaborative capabilities, finally, proved to be a key enabler for successful supplier integration.
Numerical Prediction of Non-isothermal Flow with Convective Heat Transfer Through a Rotating Curved Square Channel with Bottom Wall Heating and Cooling from the Ceiling

Received: 1 July 2019 Accepted: 9 September 2019 The present paper investigates numerical simulation of fluid flow and heat transfer through a rotating curved square channel of curvature ratios ranging from 0.001 to 0.5. Crank-Nicolson and Adams-Bashforth methods together with the function expansion and the collocation methods are applied to obtain the numerical solution. The bottom wall of the channel is heated while cooling from the ceiling. The channel is rotated in the positive direction for the Taylor number
Calculation of Critical Load for Pure Distortional Buckling of Lipped Channel Columns

This paper presents a method that allows calculating the elastic critical stress for the distortional buckling mode, based on the buckling mode classification of typical lipped channel columns. In our case, Cold-Formed Steel Lipped Channel Columns are subjected to compression. Moreover, in order to consolidate the important findings of this work, a comparative study was carried out to assess the reliability of various distortional buckling models that are provided by different design Standards. It was found that the American and Australian approaches, given in the codes of practice, are closer to the Finite Strip Method than to the European method. An analytical solution was proposed for the determination of the distortional buckling stress on the basis of a statistical method; it corresponds to lipped channel sections with a flange width to web width ratio b/h ranging from 0.1 to 1, and a lip width to web width ratio c/h between 0 and 0.5. After comparison with the results given by the finite strip method for pure distortional buckling, it turned out that the proposed approach provides a reasonable prediction for the elastic distortional buckling stress for lipped channel sections subjected to compression. In fact, this method gives better results than the American approach.
SIMULATION OF SWIRLING FLOW THROUGH NOZZLES FOR A BIDIRECTIONAL VORTEX ROCKET ENGINE

The purpose of this research is to simulate the swirling flow through a nozzle, which would be attached to the exhaust of the bidirectional vortex rocket nozzle. The simulation is conducted using a simulation software called STAR CCM+, a computational fluid dynamics program. In this numerical analysis, information is collected regarding the influence of swirling flow on the shock structure and Mach number of the nozzles. Two different nozzle geometries (conical and parabolic) are used for the simulation and the results are compared to simulations without swirling flow. The study is used to verify previous theoretical and experimental results and also to verify nozzle geometries proposed for the bidirectional vortex rocket engine design at Penn State Harrisburg. The simulations for the most part shows agreement with the experimental and theoretical results in terms of the effect of swirl on the shock structures and locations. While the shock structure is largely unchanged in the presence of swirl for the conical nozzle, a change in shock location is noticed in the parabolic nozzle case, which can be an important area of interest for further research. The study also examines the mass flow rates for the two types of flows and shows a reduction in the mass flow rate for the nozzle with swirling flow in the case of a conical nozzle.
Distributed Privacy-Preserving Prediction

In privacy-preserving machine learning, individual parties are reluctant to share their sensitive training data due to privacy concerns. Even the trained model parameters or prediction can pose serious privacy leakage. To address these problems, we demonstrate a generally applicable Distributed Privacy-Preserving Prediction (DPPP) framework, in which instead of sharing more sensitive data or model parameters, an untrusted aggregator combines only multiple models' predictions under provable privacy guarantee. Our framework integrates two main techniques to guarantee individual privacy. First, we improve the previous analysis of the Binomial mechanism to achieve distributed differential privacy. Second, we utilize homomorphic encryption to ensure that the aggregator learns nothing but the noisy aggregated prediction. We empirically evaluate the effectiveness of our framework on various datasets, and compare it with other baselines. The experimental results demonstrate that our framework has comparable performance to the non-private frameworks and delivers better results than the local differentially private framework and standalone framework.