Miracle-dz/UniFAR-FTUs huggingface dataset:
Alternating-offers bargaining, dynamic matching and threat of Bertrand competition

We consider alternating-offers bargaining between a buyer and a seller in a dynamic matching model where the appearance of a third party triggers a Bertrand -type competition between the identical agents. In the continuous-time limit, Nash' axiomatic bargaining solution holds only if buyers' and sellers' matching rates are equal. Otherwise the equilibrium sharing rule assigns a greater fraction of the surplus to the party facing less immediate threat of competition. This suggests that not only the reservation values but also the partition rule according to which the surplus is divided should be treated as endogenous in bilateral matching models. JEL Classification: D40, D43, D83.
Spectroscopic investigations of polycrystalline In x Sb 20 − x Ag 10 Se 70 ( 0 6 x 6 15 ) multicomponent chalcogenides

The composition dependence of physical properties of chalcogenides has recently been studied for their phase change properties and energy conversion. In the present work, we report the structure, composition, optical and Raman spectroscopy results for bulk polycrystalline InxSb20−xAg10Se70 (0 6 x 6 15) samples. The phase quantification and composition have been studied by using XRD and EDX techniques. The alloy composition up to 5 at. % of indium resulted in crystallization of AgSbSe2, while further increase in In content favored the formation of another chalcopyrite AgInSe2 phase yielding the solid solutions for this alloy system. A decrease in band gap up to x = 5 followed by its increase with an increase in indium concentration has been observed. The variations in shape and position of characteristic Raman bands has been used for understanding the structural modifications of the network with the variation in indium content.
Nanoclustering augmentation : a novel mechanism of Ras activation in cancer

1 SAMMANFATTNING (Swedish abstract) 2 ABBREVIATIONS 5 LIST OF ORIGINAL PUBLICATIONS 7 INTRODUCTION 8 REVIEW OF THE LITERATURE 9 1. The biology of Ras 9 1.1. Ras superfamily 9 1.2. Ras family 10 1.3. The structure of Ras 12 1.4. Ras signaling 14 1.5. Raf signaling pathway 16 1.6. Raf proteins 17 2. Organization of Ras on the membranes 20 2.1. Cellular membranes 20 2.2. The spatial dynamics of Ras in the cell 21 2.3. Nanoscale organization of Ras proteins on the membrane 25 2.4. Modulators of Ras nanoclustering 30 2.5. Galectin-1 is a regulator of H-ras nanoclustering 31 3. Ras in diseases 33 3.1. Ras in cancer 33 3.2. Ras misregulation in developmental diseases 36 AIMS OF THE STUDY 39 MATERIALS AND METHODS 40 1. Cell culture (I, II, III) 40 2. DNA constructs and molecular cloning (I, II, III) 40 3. Microscopy methods 41 3.1. Spot variation STED-FCS (I) 41 3.2. Fluorescence recovery after photobleaching (FRAP) (I) 42 3.3. Wide-field FLIM-FRET measurements (I, II, III) 43 4. PC12 cell differentiation assay (II) 46 5. Tumorigenicity assays in NIH/3T3 cells (II) 46 6. Other methods (I, II, III) 47 7. Antibodies used in WB (I, II, III) 48
Trading robust representations for sample complexity through self-supervised visual experience

Learning in small sample regimes is among the most remarkable features of the human perceptual system. This ability is related to robustness to transformations, which is acquired through visual experience in the form of weak- or self-supervision during development. We explore the idea of allowing artificial systems to learn representations of visual stimuli through weak supervision prior to downstream supervised tasks. We introduce a novel loss function for representation learning using unlabeled image sets and video sequences, and experimentally demonstrate that these representations support one-shot learning and reduce the sample complexity of multiple recognition tasks. We establish the existence of a trade-off between the sizes of weakly supervised, automatically obtained from video sequences, and fully supervised data sets. Our results suggest that equivalence sets other than class labels, which are abundant in unlabeled visual experience, can be used for self-supervised learning of semantically relevant image embeddings.
PHARMACOLOGICAL EVALUATIONS EFFECT OF THE HYDROALCOHOLIC EX DODONEIFOLIUS ON RAT TRACHEA

The present study was designed to investiga hydroalcoholic extract of Tapinanthus dodoneifolius (Ta evaluate this effect, the contractile activity of tracheal isometrically recorded. On the isolated tracheal rings effects: (a) a reduction of the contraction obtained by B strips precontracted by KCl, which was not influenced by dependent decrease of the spasm evoked by calcium c physiological salt solution, before and after intracellula effect on contraction induced by acetylcholine in supplemented with EDTA (5x10M). It is concluded th channels does not play a significant role in the re antispasmodic property of Tapidod seems to be mediated release. 3. Most likely an inhibition of the intracellular C Keys words: Extract of Tapinanthus dodoneifolius (Tapi 1 UFR/SVT Université de Ouagadougou BP 7021 BF. 2 IRSS/CNRST BP 7192 Ouagadougou BF 3 UFR/SDS Université de Ouagadougou BP 7021 BF Afr. J. Traditional, omplementary and lternative Medicines africanethnomedicines.ne FOR THE RELAXANT TRACT OF TAPINANTHUS Sylvin, OUEDRAOGO Lamini, mond, erre. 03 BP 7021 Burkina Faso. S/CNRST), BP 7192, Ouagadougou, ugou, 03 BP 7021, Burkina Faso. @yahoo.fr te the blocking of calcium by the pidod), "in vitro", on rat trachea. To chains from Wistar Kyoto rats was the extract produced the following aCl2, (b) a bronchorelaxing action, on TEA (3x10 M), (c) a concentrationhloride (CaCl2) in K -rich Ca -free + 2+ r calcium depletion (d), an inhibitory Ca -free Krebs-Heinseleit solution 2+ at: 1. The activation of the potassium laxant effect of Tapidod. 2. The by the blockade of intracellular Ca a-regulating proteins is involved. dod); Trachea; Calcium.
Psychrotolerance Mechanisms in Cold-Adapted Bacteria and their Perspectives as Plant Growth-Promoting Bacteria in Temperate Agriculture

Cold-adapted bacteria survive in extremely cold temperature conditions and exhibit various mechanisms of adaptation to sustain their regular metabolic functions. These adaptations include several physiological and metabolic changes that assist growth in a myriad of ways. Successfully sensing of the drop in temperature in these bacteria is followed by responses which include changes in the outer cell membrane to changes in the central nucleoid of the cell. Their survival is facilitated through many ways such as synthesis of cryoprotectants, cold acclimation proteins, cold shock proteins, RNA degradosomes, Antifreeze proteins and ice nucleators. Agricultural productivity in cereals and legumes under low temperature is influenced by several cold adopted bacteria including Pseudomonas, Acinetobacter, Burkholderia, Exiguobacterium, Pantoea, Rahnella, Rhodococcus and Serratia. They use plant growth promotion mechanisms including production of IAA, HCN, and ACC deaminase, phosphate solublization and biocontrol against plant pathogens such as Alternaria, Fusarium, Sclerotium, Rhizoctonia and Pythium.
SMART CAMPUS : Building-user Interaction Towards Energy Efficiency Through ICT-based Intelligent Energy Management Systems

The SMART CAMPUS project, co-funded by the European Commission (CIP-ICT-PSP no. 297251), which started in 2011 and will end in 2015, aims at increasing energy efficiency in public university buildings through a dynamic approach that involves negotiating the building environmental conditions (e.g., temperature, lighting, and ventilation) with the users, by developing ICT-based services and applications that will drive a bi-directional learning process such that both the user and the building learn how to interact with each other in a more energy efficient way. With the proposed approach, the project aims at transforming the behaviour of university campus users towards more energy efficient practices.
Hybridization of Adaptive Differential Evolution with an Expensive Local Search Method

Differential evolution (DE) is an effective and efficient heuristic for global optimization problems. However, it faces difficulty in exploiting the local region around the approximate solution. To handle this issue, local search (LS) techniques could be hybridized with DE to improve its local search capability. In this work, we hybridize an updated version of DE, adaptive differential evolution with optional external archive (JADE) with an expensive LS method, Broydon-Fletcher-Goldfarb-Shano (BFGS) for solving continuous unconstrained global optimization problems. The new hybrid algorithm is denoted by DEELS. To validate the performance of DEELS, we carried out extensive experiments on well known test problems suits, CEC2005 and CEC2010. The experimental results, in terms of function error values, success rate, and some other statistics, are compared with some of the state-of-the-art algorithms, self-adaptive control parameters in differential evolution (jDE), sequential DE enhanced by neighborhood search for large-scale global optimization (SDENS), and differential ant-stigmergy algorithm (DASA). These comparisons reveal that DEELS outperforms jDE and SDENS except DASA on the majority of test instances.
A Sustainable Additive Approach for the Achievement of Tunable Porosity

This study aims to design a green additive approach for the fabrication of controlled porosity on hydrogels. Although hydrogels have been of common use in tissue engineering, the generation of controllable porosity remains an issue due to their swelling and degradation properties. Hydrogels in this study were fabricated by physical cross-linking and the porosity was generated by casting the solution in a 3D printed mold prior to physical cross-linking. This approach eliminates the use of chemical cross-linking compounds which are often toxic and not environmentally friendly. Polyvinyl alcohol was selected to validate this technique due to its biocompatibility and adequate mechanical properties. The microstructure, mechanical properties and deformation of the porous hydrogels were characterized. Results revealed that the proposed bioplotting technique reduced variation of pore size and allotted for the realization of controlled and tunable pore structures.
Antibiotic Resistance Mechanisms in Bacteria: Relationships Between Resistance Determinants of Antibiotic Producers, Environmental Bacteria, and Clinical Pathogens

Emergence of antibiotic resistant pathogenic bacteria poses a serious public health challenge worldwide. However, antibiotic resistance genes are not confined to the clinic; instead they are widely prevalent in different bacterial populations in the environment. Therefore, to understand development of antibiotic resistance in pathogens, we need to consider important reservoirs of resistance genes, which may include determinants that confer self-resistance in antibiotic producing soil bacteria and genes encoding intrinsic resistance mechanisms present in all or most non-producer environmental bacteria. While the presence of resistance determinants in soil and environmental bacteria does not pose a threat to human health, their mobilization to new hosts and their expression under different contexts, for example their transfer to plasmids and integrons in pathogenic bacteria, can translate into a problem of huge proportions, as discussed in this review. Selective pressure brought about by human activities further results in enrichment of such determinants in bacterial populations. Thus, there is an urgent need to understand distribution of resistance determinants in bacterial populations, elucidate resistance mechanisms, and determine environmental factors that promote their dissemination. This comprehensive review describes the major known self-resistance mechanisms found in producer soil bacteria of the genus Streptomyces and explores the relationships between resistance determinants found in producer soil bacteria, non-producer environmental bacteria, and clinical isolates. Specific examples highlighting potential pathways by which pathogenic clinical isolates might acquire these resistance determinants from soil and environmental bacteria are also discussed. Overall, this article provides a conceptual framework for understanding the complexity of the problem of emergence of antibiotic resistance in the clinic. Availability of such knowledge will allow researchers to build models for dissemination of resistance genes and for developing interventions to prevent recruitment of additional or novel genes into pathogens.
Significance of incompatibility reactions of Rhizobium japonicum strains with soybean host genotypes.

A sample of soybean [Glycine max (L.) Merr. ] plant introductions from Asia, representing maturity groups 00 through X, was tested for the presence of the Rj2 and Rj4 genes. Both of these genes condition ineffective nodulation responses: Rj2, specifically with the cl and 122 serogroups of Rhizobium japonicum; Rj4, with R. japonicum strain 61. Rj2 was present in 19 of the 851 fines tested. The 19 lines were in maturity groups III to VIII and most originated from China and Japan. Rj4 was present in 261 of the 851 lines tested, and was most prevalent in lines from southeast Asia. This gene occurred in lines from maturity groups 00 to X and was most frequent in Group X with 94% of the lines possessing it. This evidence of geographical differences in gene frequencies suggests that the combinations of host and Rhizobium ecotypes which coevolved in Asia may have been disrupted through separate introduction of the host and microsymbiont to the New World. If this is the case, N2 fixation may be improved by reassembling the host/strain combinations that evolved in Asia. Use of incompatibility responses may enable soybean breeders to control host specification of symbiosis with genetically improved Rhizobium strains. Host compatibility with indigeneous Rhizobium strains may profoundly affect performance of some plant introductions in evaluation nurseries on soils of low N fertility. Management of N fertility in such nurseries will depend on breeders' objectives.
A calibrated dual-wavelength infrared thermometry approach with non-greybody compensation for machining temperature measurements

We report the development of a new approach for determining temperatures using the dual-wavelength infrared thermometry technique, which does not presume greybody behaviour and compensates for the spectral dependence of emissivity. This approach is based on Planck's radiation equation and explicitly accounts for the wavelength-dependent response of the IR detector and the losses occurring due to each of the elements of the IR imaging system that affect the total radiant energy sensed in different spectral bands. A thorough calibration procedure is utilized to determine a compensation factor for the spectral dependence of emissivity, which is referred to as the non-greybody compensation factor (NGCF). Calibration and validation experiments are carried out on Aluminum 6061-T6 targets with two different surface roughnesses. Results show that this alloy does not exhibit greybody behaviour, even though the two spectral bands used were relatively close to each other, and that the spectral dependence of emissivity is influenced by the surface finish. It is found that non-greybody behaviour of low emissivity surfaces can lead to significant systematic error in dual-wavelength IR thermometry. The inclusion of the NGCF eliminates the systematic error caused by the invalidity of greybody assumption and thus improves the accuracy of the measurements. Non-greybody-compensated dual-wavelength thermography is used to measure the chip temperature along the tool–chip interface during orthogonal cutting of Al 6061-T6 and sample results at three different cutting speeds are presented.
Comparison of Activated Clotting Time Analyzer in Cardiovascular Surgery

Accurate control of the anticoagulation level is important for safe initiation of cardiopulmonary bypass. Activated clotting time (ACT) has been used to monitor heparin therapy in cardiovascular surgery to prevent thrombosis in extracorporeal circulation. It is first introduced in 1966 by Hattersley to measure the time required for whole blood samples to clot after contact activation.1 The most commonly used automatic method for ACT derivation is Hemochron 401 (ITC, International Technidyne Corp., Edison, NJ),which registers ACT in seconds by a mechanical device using celite, a diatomaceous earth, as activator. Though it is widely adopted in cardiovascular surgery and other intervention cardiologist laboratories, it has some weakness such as poor sensitivities, reproducibility, and the variability after heparin injection is large [1].
Fault Diagnosis with Evolving Fuzzy Classifier Based on Clustering Algorithm and Drift Detection

The emergence of complex machinery and equipment in several areas demands efficient fault diagnosis methods. Several fault diagnosis methods based on different theories and approaches have been proposed in the literature. According to the concept of intelligent maintenance, the application of intelligent systems to accomplish fault diagnosis from process historical data has been shown to be a promising approach. In problems involving complex nonstationary dynamic systems, an adaptive fault diagnosis system is required to cope with changes in the monitored process. In order to address fault diagnosis in this scenario, use of the so-called “evolving intelligent systems” is suggested. This paper proposes the application of an evolving fuzzy classifier for fault diagnosis based on a new approach that combines a recursive clustering algorithm and a drift detection method. In this approach, the clustering update depends not only on a similarity measure, but also on the monitoring changes in the input data flow. A merging cluster mechanism was incorporated into the algorithm to enable the removal of redundant clusters. Multivariate Gaussian memberships functions are employed in the fuzzy rules to avoid information loss if there is interaction between variables. The novel approach provides greater robustness to outliers and noise present in data from process sensors. The classifier is evaluated in fault diagnosis of a DC drive system. In the experiments, a DC drive system fault simulator was used to simulate normal operation and several faulty conditions. Outliers and noise were added to the simulated data to evaluate the robustness of the fault diagnosis model.
The Effect of the Case-Based Learning Method on High School Physics Students' Conceptual Understanding of the Unit on Energy.

The purpose of this research was to examine the effects of two different methods of teaching physics (Case-based Learning and Traditional Instruction) on the conceptual understanding of 9th-grade students regarding topics related to energy. The research was conducted in two different 9th-grade classes in a high school. The research used a pretest/post test quasi-experimental method with a nonequivalent control group. The research was carried out with two groups--a study group (n=30) and a control group (n=30). The Study group were instructed using the method of Case-Based Learning while the control group were approached with traditional teaching methods. Data for the research were collected using the "Energy Conceptual Test. " The data collected were analyzed in the SPSS 15.0 statistics program in terms of frequency, percentages, arithmetic means, and standard deviation. When the results of the study were examined as to the changes in the conceptual understanding attained in the two groups (on a question basis), it was found that the most positive change could be seen in the case story group.
The metabolic costs of gardening tasks in children.

The metabolic cost of 10 gardening tasks was measured in children to determine the exercise intensities associated with these tasks. Seventeen children [(mean ± SD) aged 12.4 ± 0.7 years and body mass index 21.6 ± 4.0 kg m] participated in this study. The children performed the 10 gardening tasks at a garden previously established in Cheongju, Chungbuk, South Korea. They visited the garden twice and performed five different tasks on each visit. Five minutes were provided to complete each gardening task and a 5-minute rest was allowed between each task. The children wore a portable telemetric calorimeter and a heart rate monitor for measurement of oxygen uptake and heart rate during the gardening tasks. The results show that the 10 gardening tasks represented moderateto highintensity physical activity for the children [4.3 ± 0.5 to 6.6 ± 1.6 metabolic equivalents (MET)]. Digging (6.6 ± 1.6 MET) and raking (6.2 ± 1.5 MET) were high-intensity physical activities, and digging was more intense than the other gardening tasks performed in this study (P < 0.05). Tasks such as weeding (5.8 ± 1.1 MET), mulching (5.5 ± 1.3 MET), hoeing (5.3 ± 0.7 MET), sowing seeds (5.0 ± 1.1 MET), harvesting (4.8 ± 0.6 MET), watering (4.6 ± 1.1 MET), mixing growing medium (4.4 ± 0.6 MET), and planting transplants (4.3 ± 0.5 MET) were moderate-intensity physical activities. The MET data for the gardening tasks will facilitate the development of garden-based exercise interventions for children, which can promote health and physically active lifestyle.
Image Filtering and Registration by using Hybrid Area and Feature Based Method

During acquisition and transmission, noise can be introduced into images. The main problem of image processing is to effectively remove noise from an image, but keep its features intact. The impulse noise is removed by using Gaussian filter. This filtering process assumes a Gaussian spatial profile in the neighborhood of noisy pixel. Image registration can be defined as the process of transformation of various image data sets into one co-ordinate system. The need of image registration is its ability to compare or integrate the data obtained from the different measurements. For any image registration, filtering is necessary to remove the noise. Image registration is classified into image segmentation and Scale invariant feature transformation. The last process is the template matching. This method provides best filtering at higher noise density. It also provides maximum cross correlation coefficient for registered images. Key points: Gaussian noise, K-means clustering algorithm, Scale invariant Feature transform, Affine Transform, Template matching.
USING EXPERT KNOWLEDGE TO INFORM MULTIVARIATE ANALYSES

This paper outlines methods and reasoning that advocate for the use of expert Coach and Athlete knowledge in support of mutivariate analyses in Sport Biomechanincs and related disciplines. It argues that human movement research involving the collection of multiple dependent variables suffers similar problems to other areas of behavioural science, in that models proposed for analyses are inadequately constrained by other data and are vulnerable to a-posteori modification that lacks sound theoretical or evidential justification. An approach is presented where expert accounts of how successful movements are performed are captured and analysed qualitatively, in order to present data themes that may be used to identify important events and variables for analyses when quantitatively examining movement. This paper argues for the utility of a specific mixed-methods approach to movement research involving multiple dependent variables.