Miracle-dz/UniFAR-FTUs huggingface dataset:
Roles of Additional Information for Wayfinding in Virtual Environment

Although variety of artificial information such as a roadmap and a car-navigation system are available, our primary information for wayfinding is cognitive map, namely internal representation of an environment. Since an allocentric cognitive map is learned through exploring the environment with egocentric view, transformation from observer-centered frame of reference to worldcentered frame of reference is necessary. We simulated wayfinding in a real-world environment by a maze in a virtual-reality display system. We investigated effects of additional information to egocentric view during exploration of the environment on performance of cognitive map acquisition. Performance was evaluated by accuracy of learned cognitive. The results showed that with addition of landmarks on the maze there was not only statistically significant improvement of acquired cognitive map but shorter time to take for learning. It was also found that when information about heading direction was presented with egocentric view, performance was significantly better than when no additional information was presented. These results suggest that transformation from observer-centered frame of reference to world-centered frame of reference requires information about observer's orientation besides temporal change of egocentric view.
Computer-supported Interactive Assignment of Keywords for Literature Collections

A curated literature collection on a specific topic helps researchers to find relevant articles quickly. Assigning multiple keywords to each article is one of the techniques to structure such a collection. But it is challenging to assign all the keywords consistently without any gaps or ambiguities. We propose to support the user with a machine learning technique that suggests keywords for articles in a literature collection browser. We provide visual explanations to make the keyword suggestions transparent. The suggestions are based on previous keyword assignments. The machine learning technique learns on the fly from the interactive assignments of the user. We seamlessly integrate the proposed technique in an existing literature collection browser and investigate various usage scenarios through an early prototype.
The Analysis of Manufacturing System Utilization by Using Queuing and Taylor Theories

The manufacturing industry continues to develop rapidly and has since become an important catalyst to the country’s economic growth. So, the manufacturing environments are becoming highly competitive. Queuing theory and Taylor theory are analytical models that will be used to analyze capacity usage of manufacturing. This study examines the utilization of production facilities in an automotive industry based on the application of queuing theory and Taylor theory. This study was conducted in machining department and only focused on production of oil pump product. The validation of resulting utilization values, through comparing them with the utilization value, was based on the company database. Based on this validation result, the effectiveness between Queuing theory and Taylor theory in analyzing the utilization of production line can be determined. The finding displayed that the effectiveness of Queuing theory is better than the effectiveness of Taylor theory.
Lipid based particulate formulations for the delivery of antigen

Particulate adjuvant systems are largely classified according to their functional characteristics, such as the nature of the typical immune response they induce, or their perceived mode of action. From a formulation science perspective, it is practical to classify antigen delivery systems according to the physical nature of the formulations. This article discusses lipid based particulate systems, grouped according to the nature of their predominant lipid constituent.
ROBUST DESIGN OF COMPRESSOR CASCADE AIRFOILS , USING EVOLUTIONARY ALGORITHMS AND SURROGATE MODELS

The aim of this paper is to present and test an optimization method for the design of turbomachinery blade airfoils with optimal performance at given flow conditions and the additional requirement that this performance remains (almost) constant even in the presence of slight manufacturing–assembling errors or slight shape changes during the operation. The proposed method goes a step beyond standard design tools ensuring the robustness of the designed shapes under uncertainties related to the design variables. The basic optimization tool is a multi–objective evolutionary algorithm, which cooperates with two kinds of evaluation tools. All blade airfoils are evaluated, at the nominal flow conditions, using an integral boundary layer method coupled with an inviscid flow solver. Changes in performance, due to changes in shape are quantified through the “massive” use of inexpensive, surrogate evaluation models. The use of surrogate models requires an initial database of evaluated samples. The sampling is carried out by means of a new, kriging-based search algorithm aiming at minimizing the database size together with the relevant CPU cost. In the course of this incremental algorithm, the new database point is the one for which kriging yields the most uncertain prediction. The robust design of a compressor cascade airfoil is demonstrated.
Monoclonal antibodies raised against 167–180 aa sequence of human carbonic anhydrase XII inhibit its enzymatic activity

Abstract Human carbonic anhydrase XII (CA XII) is a single-pass transmembrane protein with an extracellular catalytic domain. This enzyme is being recognized as a potential biomarker for different tumours. The current study was aimed to generate monoclonal antibodies (MAbs) neutralizing the enzymatic activity of CA XII. Bioinformatics analysis of CA XII structure revealed surface-exposed sequences located in a proximity of its catalytic centre. Two MAbs against the selected antigenic peptide spanning 167–180 aa sequence of CA XII were generated. The MAbs were reactive with recombinant catalytic domain of CA XII expressed either in E. coli or mammalian cells. Inhibitory activity of the MAbs was demonstrated by a stopped flow CO2 hydration assay. The study provides new data on the surface-exposed linear CA XII epitope that may serve as a target for inhibitory antibodies with a potential immunotherapeutic application.
Time Domain Parameter Distribution Estimation in Dispersive Media

The Cole-Cole model is known to accurately describe the dielectric response of a dispersive material over a wide range of frequencies. The model, however, does not lend itself easily to fast, efficient time domain simulation methods such as the Finite Difference Time Domain (FDTD) method. Instead the physics-based Debye model (of which the Cole-Cole model is a non-physical, heuristic generalization) is often used. However, simulations do not match data over any broad range of frequencies. In this work, we seek to avoid the difficulty of implementing the Cole-Cole model by presenting an approximation of dispersive mechanisms using distributions of parameters within the Debye model. Thus, parameter estimation becomes an inverse problem for the distribution of dielectric parameters. We formulate and solve this inverse problem in the case of time-domain electric field data. The forward problem requires a fast FDTD implementation capable of incorporating distributions of parameters. Introduction A fundamental question in electromagnetics is how to model dispersion and dissipation of the fields in complex materials such as biological tissue. This has most often led to the use of Maxwell’s equations coupled with constitutive relationships for polarization. The problem is even more difficult with noisy data or variability (heterogeneity) in the material being interrogated. Some deterministic models have been generalized to an extent that they seem to account for this variability, but there is some question as to whether the resulting models are even physically realistic. A recently rediscovered modeling framework allows uncertainty at the molecular level through distributions of parameters representing molecular variability. Intensive experimental efforts have been pursued in describing data for complex materials in the frequency domain with distributions of dielectric parameters, especially relaxation times in multiple Debye models. A significant amount of this work is reviewed in the survey paper by Foster and Schwan[5]. The corresponding time-domain inverse problems were initially developed in [1] and examples for a one dimensional case were solved in [2] using finite elements for the forward simulation and quadrature for computing the expected value over a distribution. Our contribution here is to implement a fast forward solver utilizing the generalized Polynomial Chaos framework. This allows use of the finite difference time domain (FDTD) method for solving the dispersive Maxwell’s Equations and eliminates the need for a separate computation of expected values. Maxwell’s equations may be coupled with constitutive laws to include effects from polarization
Regulating potential assessment of individual electro-heating load using similarity-based Suport Vector Machine

The power supply side regulating capability of the power grid is limited, and it is important to dig deep into the load side regulation capability. Electro-heating load is a time-shifting load with the characteristics of small thermal inertia, fast response, high controllability, etc. It has the potential to participate in active power dispatching and control the power grid. When the electro-heating load is working, the indoor temperature curve is affected by many factors. It has a similar influence characteristic quantity, and a similar temperature rise and fall process is exhibited in the temparature setted range. When using the traditional equivalent thermal parameter to evaluate, the outdoor temperature at the end of the warming up or cooling down process is unknown, so the regulating potential of individual electro-heating load cannot be accurately evaluated. Therefore, this paper proposes a similarity-based support vector machine single electro-heating regulating potential evaluation method, and compared with the traditional equivalent thermodynamic model, it shows that this method has higher evaluation accuracy.
A New Mapping Method for Matching Stereo Images

Passive stereo vision is a well known approach for recovering 3D information from two or more video images. The key task is the so-called correspondence problem. It consists of identifying features in the left and right images that are projections of the same physical feature in the three-dimensional space. This paper presents a simple and fast algorithm to solve the stereo correspondence problem. In our method, the problem is first mapped onto a two dimensional matrix, called matching matrix. The correspondence problem is then formulated in terms of finding pairs of true matches that satisfy local and global constraints. Local constraints are used to discard incompatible matches whereas global ones are used to search best matches. Experimental results are presented to demonstrate the effectiveness of the proposed approach for real-time obstacle detection using linear stereo vision. Key-Words: Image processing, Linear stereo vision, Obstacle detection, Real-time processing, Stereo matching.
An Online Delay-Optimal Iterative Multiclass Scheduler for Generic M 2 M Uplink

The uplink Machine-to-Machine (M2M) traffic is fairly heterogeneous in its delay-requirements both across the sensor nodes within a network and also across different M2M applications. Therefore, in this letter, we classify the uplink M2M traffic into multiple classes (based on delay requirements) and propose a delay-optimal multiclass packet scheduler that ensures proportional fairness of service to all classes. We accommodate the diverse delay requirements in our framework using generic sigmoidal utility functions of service delay. We note that any work-conserving scheduling policy can be realized by appropriately time-sharing between all possible preemptive priority policies. Then the optimal scheduler is determined iteratively by solving for the optimal fraction of time-sharing between all priority scheduling policies, that results in maximum system utility. The proposed scheduler can be implemented online with reduced computational complexity due to its iterative nature. Using Monte-Carlo simulations, we verify the optimality of the proposed iterative scheduler and show that it outperforms othe r state-of-the-art packet schedulers.
Hybrid Strategy and Competitive Strategy : Evidence from Northern States SMEs in Malaysia

The fact that business environments is becoming complex cannot be ignored and numerous numbers of companies are tirelessly exploring business plans to adopt for their survival most especially Small Medium Enterprises (SMEs). This study intended to explore how SMEs can achieve advantage in respect to competition in Malaysia setting. The key target of this study was to establish the type of business`strategies that are most suitable in the context of northern part of Malaysia. This study`s sample covered SMEs in the northern part of Malaysia which consists of the states like Penang, Perlis and Kedah. This study`s population was obtained from SMEs directory via SMEs` website. A purposive sampling was used and a cross sectional study was conducted whereby collection of data was carried out over a period of weeks with the use of questionnaires which were mailed to respondents and administered individually. This study`s result advocates that most business strategies were essential to SMEs. In addition, it is equally pointed out that most SMEs utilize combination of Porter`s generic strategies or hybrid whereby below half of the sampled population focusing on one type of strategy (focus and differentiation and cost leadership). This study finds out that in order to retain competitive status in the business, SMEs should adopt the use of combined business strategies. For this reason, it is strongly indicated that Porter Generic Strategies are still appropriate for carrying out SMEs in the northern parts of Malaysia; the setting of this study.
Treatment of Otitis Media With Cefuroxime Axetil

Cefuroxime axetil and cefaclor were compared for efficacy in the treatment of acute otitis media with effusion. Sixty-four pediatric outpatients had tympanocentesis for culture, and then were randomized to a ten-day course of treatment with cefuroxime axetil or cefaclor. Streptococcus pneumoniae and Haemophilus influenzae were isolated from 25 (39%) and 23 (36%) patients, respectively. Treatment was beneficial in 26 (90%) of the patients who received cefuroxime axetil, and in 16 (76%) of the cefaclor-treated patients. Treatment failed in five (24%) of the cefaclor-treated patients, and in only three (10%) patients who received cefuroxime axetil. Haemophilus influenzae was the initial causative pathogen in a disproportionate number of treatment failures. This study demonstrates the efficacy of cefuroxime axetil in the treatment of otitis media.
Delta Debugging Microservice Systems with Parallel Optimization

Microservice systems are complicated due to their runtime environments and service communications. Debugging a failure involves the deployment and manipulation of microservice systems on a containerized environment and faces unique challenges due to the high complexity and dynamism of microservices. To address these challenges, we propose a debugging approach for microservice systems based on the delta debugging algorithm, which is to minimalize failure-inducing deltas of circumstances (e.g., deployment, environmental configurations). Our approach includes novel techniques for defining, deploying/manipulating, and executing deltas during delta debugging. In particular, to construct a (failing) circumstance space for delta debugging to minimalize, our approach defines a set of circumstance dimensions that can affect the execution of microservice systems. To automate the testing of deltas, our approach includes the design of an infrastructure layer for automating deployment and manipulation of microservice systems. To optimize the delta debugging process, our approach includes the design of parallel execution for delta testing tasks. Our evaluation shows that our approach is scalable and efficient with the provided infrastructure resources and the designed parallel execution for optimization. Our experimental study on a medium-size microservice benchmark system shows that our approach can effectively identify failure-inducing deltas that help diagnose the root causes.
Methods for estimating volume , biomass and tree species diversity using field inventory and airborne laser scanning in the tropical forests of Tanzania

VIII List of papers . IX 1.0. Introduction . 1 1.1. Tropical forests and REDD+ . 1 1.2. Status of forest resources and REDD+ MRV system in Tanzania . 3 1.3. Rationale for the study . 5 2.0. Research objectives . 6 3.0. Background . 7 3.1. Analytical conceptual framework of the thesis . 7 3.2. Tree AGB and volume models . 8 3.3. Remote sensing support for forest inventory . 9 3.3.1. Modelling and predicting AGB using ALS data . 9 3.3.2. Effects of field plot size on prediction accuracy of AGB in ALS-assisted inventories . 11 3.3.3. Modelling and predicting measures of tree species diversity using ALS data . 12 4.0. Materials and methods . 13 4.1. Study sites . 13 4.2. Data collection . 15 4.2. 1. Destructive sampling data . 15 4.2. 2. Field inventory data . 15 4.2. 3. Remotely sensed data . 17 4.3. Data analyses . 18 5.0. Main findings and discussion . 19 5.1. Tree volume models for miombo woodlands . 19 5.2. Modelling AGB using ALS data . 20 5.3. Effects of field plot size on prediction accuracy of AGB in ALS-assisted inventories 21 5.4. Modelling measures of tree species diversity using ALS data . 22 6.0. Conclusions and future studies . 24 References . 28 Appendix: Papers I-IV
Maximising Genetic Response in Tree Breeding with Constraints on Group Coancestry

This study compares 4 methods to maximize response to selection while minimizing the inbreeding that accumulated over 6 generations of selection. A selection algorithm is described which maximizes the mean estimated breeding value of the selected trees while constraining the average coancestry among them and hence the status effective number of the population. This algorithm resulted in increased selection response, at a lower, target average coancestry level, compared to truncation selection. However the target average coancestry level for each generation is arbitrarily chosen. A variation of the algorithm is described which attempts to maximize response over 12 generations allowing for the decline in genetic variance caused by inbreeding. This leads to faster genetic gain and higher coancestry than typical tree breeding programs. Once the selection has been carried out, a mate allocation algorithm arranges matings which give each parent the number of offspring required by the selection algorithm and which minimizes inbreeding in the offspring per mating. This delays the appearance of inbreeding by at least one generation but does not alter the long term rate of inbreeding. The combination of the selection and mating algorithms lead to breeding programs requiring less controlled pollinations than truncation selection with random mating and hence reduce the cost of the breeding program.
The Impact of Total Quality Management on Firm ’ s Organizational Performance

This paper investigates the impact of Total Quality Management (TQM) on Organizational Performance. Data are collected from manufacturing firms in the republic of Cameroon. Variables used to capture Total Quality Management (TQM) are management commitment through leadership, Quality control, inspection, employee training, customer focus, benchmarking as the basis for enhancing product quality. Organizational performance is measured by Customer Satisfaction, Corporate Social responsibility, Cost Reduction, and Employee Satisfaction. We run a series of multiple regressions of organizational performance variables on explanatory variables defining TQM. Our results show that only employment training and empowerment has a significant impact on financial performance and corporate social responsibility; leadership commitment, quality control and inspection have a significant impact on cost reduction. However, none of the TQM practices appear to have a significant effect on customer satisfaction.
2 P-07 ADAMTSl as a hypoxia sensing biomarker

Objective: The ADAMTSs (a disintegrin and metalloproteinase with thrombospondin motifs) are a group of extracellullar, multidomain proteases that are found both in mammals and invertebrates whose known functions include: (i) collagen processing as pro collagen N-proteinase; (ii) cleavage of matrix proteoglycans; (iii) inhibition of angiogenesis: and (iv) blood coagulation homoeostasis [1]. We have previously reported that ADAMTS 1 was strongly and transiently expressed in the infarcted heart. Recently we have reported that ADAMTSl in induced by hypoxia [2]. These data indicated that ADAMTS 1 is a hypoxia-inducible gene. Interestingly, its expression is induced by a few hours' hypoxia (i.e., acute ischemia). The aim of this study is to test the hypothesis that whether ADAMTSl promoter can be used for detecting acute hypoxia. Methods: We cloned the human ADAMTS 1 promoter region. To determine which region is responsible for hypoxic induction of ADAMTSl, we prepared several different constructs with different length of promoter region of ADAMTS 1. We made green fluorescence protein (GFP) expressing construct under the control of the ADAMTS 1 promoter. We transfected GFP construct into human umbilical vein endothelial cells (HUVEC), and examined GFP production under 3,6, or 24 hours of hypoxia. After incubation, cells were fixed using 4% paraformaldehyde (PFA) and observed under the fluorescence microscope. Results: When GFP-transfected HUVEC were cultured in normoxic condition, GFP was very slightly observed. In contrast, a considerable number of GFP-positive HUVEC was observed when exposed to 3h hypoxia. GFP fluorescence and nearly returned to the normoxic level at 24h.
Delayed Endolymphatic Hydrops and its Relationship to Meniere's Disease

Delayed endolymphatic hydrops (EH) can be characterized as having ipsilateral and contralateral types. They are similar in that both have early and late phases of otologic symptoms and that the early phase is a profound hearing loss in one ear. The late phases differ, however, in that the ipsilateral type develops the symptoms of EH (episodic vertigo) in the deaf ear and the contralateral type develops the symptoms of EH (fluctuating hearing loss and/or episodic vertigo) in the hearing ear. In more than half the cases of both types of delayed EH, the profound hearing losses in the early phase are simply discovered to be present in early childhood without a known time of onset. The temporal bones of two patients with contralateral delayed EH show pathologic changes in the deaf ears that are similar to those known to occur in mumps and measles labyrinthitis, whereas the pathologic changes in the hearing ears are similar to those known to occur in Meniere's disease. These observations support the proposition that Meniere's disease may occur as a delayed sequela of inner ear damage sustained during an attack of subclinical viral labyrinthitis occurring in childhood.