Miracle-dz/UniFAR-FTUs huggingface dataset:
Complex problems in entrepreneurship education: Examining complex problem-solving in the application of opportunity identification

In opening up the black box of what entrepreneurship education (EE) should be about, this study focuses on the exploration of relationships between two constructs: opportunity identification (OI) and complex problem-solving (CPS). OI, as a domain-specific capability, is at the core of entrepreneurship research, whereas CPS is a more domain-general skill. On a conceptual level, there are reasons to believe that CPS skills can help individuals to identify potential opportunities in dynamic and nontransparent environments. Therefore, we empirically investigated whether CPS relates to OI among 113 masters students. Data is analyzed using multiple regressions. The results show that CPS predicts the number of concrete ideas that students generate, suggesting that having CPS skills supports the generation of detailed, potential business ideas of good quality. The results of the current study suggest that training CPS, as a more domain-general skill, could be a valuable part of what should be taught in EE.
Itm2a Expression in the Developing Mouse First Lower Molar, and the Subcellular Localization of Itm2a in Mouse Dental Epithelial Cells

Itm2a is a type II transmembrane protein with a BRICHOS domain. We investigated the temporospatial mRNA and protein expression patterns of Itm2a in the developing lower first molar, and examined the subcellular localization of Itm2a in murine dental epithelial (mDE6) cells. From the initiation to the bud stage, the in situ and protein signals of Itm2a were not detected in either the dental epithelial or mesenchymal cells surrounding the tooth bud. However, at the bell stage, these signals of Itm2a were primarily observed in the inner enamel epithelium of the enamel organ. After the initiation of the matrix formation, strong signals were detected in ameloblasts and odontoblasts. Itm2a showed a punctate pattern in the cytoplasm of the mDE6 cells. The perinuclear-localized Itm2a displayed a frequent overlap with the Golgi apparatus marker, GM130. A tiny amount of Itm2a was colocalized with lysosomes and endoplasmic reticulum. Minimal or no overlap between the Itm2a-EGFP signals with the other organelle markers for endoplasmic reticulum, lysosome and mitochondria used in this study noted in the cytoplasm. These findings suggest that Itm2a may play a role in cell differentiation during odontogenesis, rather than during the initiation of tooth germ formation, and may be related to the targeting of proteins associated with enamel and dentin matrices in the secretory pathway.
Ceramide binds to the CaLB domain of cytosolic phospholipase A2 and facilitates its membrane docking and arachidonic acid release

Excessive production of eicosanoids is characteristic of many inflammatory diseases. In this study we show that ceramide, which is an early messenger of inflammatory cytokine action, exerts a dual effect on the cytosolic phospholipase A2 (cPLA2), the rate‐limiting enzyme in arachidonic acid release and subsequent eicosanoid formation. Stimulation of renal mesangial cells with exogenous short‐chain ceramide analogs for 30 and 60 min leads to a concentration‐dependent increase in arachidonic acid release that is not blocked by specific inhibitors of mitogen‐activated protein kinase pathways. This suggests that these established upstream activators of cPLA2 are not involved in ceramide‐induced arachidonic acid release. By use of photoactivatable ceramide analogs, D‐ and L‐ [125I]3‐trifluoromethyl‐3‐(m‐iodophenyl)diazirineceramides (TID‐ceramides), we observed a direct interaction of ceramide with cPLA2. This interaction was independent of the absolute configuration as D‐ and L‐TID‐ceramide were equally effective in binding to cPLA2. Moreover, recombinant CaLB domain of cPLA2 as well as a mutant deficient in the connecting ‘hinge’ domain of cPLA2, efficiently bound D‐ and L‐TID‐ceramides, whereas the catalytic domain did not interact with TID‐ceramides. In vitro binding assays reveal that stearoyl‐arachidonyl‐phosphatidylcholine (SAPC)‐liposomes containing increasing mol% of ceramide lead to an increased association of recombinant cPLA2 to the liposomes. Furthermore, measurement of cPLA2 activity in vitro shows that the presence of SAPC‐liposomes resulted in only weak cPLA2 activity. However, the activity dramatically increases by addition of ceramide to the liposomes. Furthermore, liposomes containing SAPC and sphingomyelin resulted in no better substrate than SAPC liposomes, unless bacterial sphingomyelinase was added to generate ceramide, which then causes a marked increase in cPLA2 activity. These results demonstrate that ceramide can interact directly with cPLA2 via the CaLB domain and thereby serves as a membrane‐docking device that facilitates cPLA2 action in inflammatory diseases.
In Pursuit of Passion: A Frame Analysis of the Popular Management Literature

As business organisations move into late modernity many are shifting their emphasis from rational bureaucratic style management to one that incorporates qualities such as passion. However, despite their increasing popularity buzz-words or lay concepts such as passion are notoriously difficult to reinterpret into theoretical language. This research examines how passion has been constructed in the popular management literature. Using frame analysis, two macro frames were identified. One constructs passion as an extrinsic quality, one that leads to desired ends. The other constructs passion as an intrinsic quality, a desired end in itself. Although an important first step toward making passion more conceptually coherent, the analysis of these frames highlights a number of tensions that need to be resolved. In this way passion can become a useful theoretical construct in the sociology of work, bodies and emotions.
Intelligent Coordinates and Collective Intelligence: A case study in improving Simulated Annealing in the bin-packing domain

Consider a set of non-cooperative agents acting in an environment in which each agent attempts to maximize a private utility function. As each agent maximizes its private utility we desire a global ”world” utility function to in turn be maximized. The inverse problem induced from this situation is the following: How does each agent choose his move so that while he optimizes his private utility, the world utility is optimized as well? This problem has been considered by the theory of COllective INtelligence (COIN) (Wolpert & Tumer 2000). This paper focuses on a method for improving a class of search algorithms using Intelligent RL based learning players engaging in a non-cooperative game. The players or ”coordinates” use a more traditional AI approach to learning in a system in which largely the state of the world is not known, and effects of each agent’s actions on the world are not known a priori, and must be discovered. This is essentially a search problem through the possible policies of each coordinate of the underlying system. Search algorithms such as Simulated Annealing, Swarm Intelligence, and Genetic Algorithms, that tradeoff between exploration and exploitation are particularly useful in solving systems of this nautre, because they search directly in the space of RL policies, and try to select optimal policies which pay over time through simulation of indirect learning via optimization of the system; however, these algorithms all have one major drawback: They do not rely on the previous experiences of players in the system to help determine which actions the players should take next. This major drawback leads Wolpert and Tumer to develop a new method for improving search algorithms, Intelligent Coordinates(Wolpert, Tumer, & Bandari ). Intelligent Coordinates use RL to remember and ”learn” how to better solve the system, by applying traditional RL techniques to the exploration stage of these search algorithms. The algorithm improves the bin-packing simulation by an order of magnitude, and increases linearly with the number of items added. We present a more detailed explanation of the Intelligent Coordinates algorithm, and discuss two implementations of the bin-packing simulation that we have constructed in Java, one that uses Simulated Annealing to solve, and one that uses Intelligent Coordinates. Further, we contribute an efficient method for processing time-weighted sums, which are needed in the simulation. We also formalize a method for calculating the time-weighted probabilities of picking a particular bin B in the simulation. These probabilities are used to ”mask” the original SA distribution to achieve the more relevant IC probability distribution. We also present some original experiments in the bin-packing simulation that were not present in the original paper(Wolpert, Tumer, & Bandari ). Introduction,Multiagent Bin-Packing
The Opiate of the Masses: Measuring Spiritual Bypass and Its Relationship to Spirituality, Religion, Mindfulness, Psychological Distress, and Personality

This article discusses the development of the Spiritual Bypass Scale-13 (SBS-13). Spiritual bypass is a clinical process of avoiding difficult psychological material using spiritual beliefs, practices, or experiences. A major limitation to the literature on spiritual bypass is that no psychometrically sound measures of the phenomenon exist, thus preventing scholars and clinicians from understanding its causes and treatment implications beyond anecdotal case reports. The SBS-13 was developed using a community sample of 661 participants. The factor structure of the SBS-13 was investigated using exploratory and confirmatory factor analysis which identified 2 facets (Psychological Avoidance and Spiritualizing) with a second order facet (Spiritual Bypass). The reliability of SBS-13 was satisfactory, with alpha coefficients ranging from . 75 to . 87 across 2 different samples. The convergent, discriminant, predictive, and incremental validity of the SBS-13 was assessed using several criterion variables including measures of spirituality, religiosity, religious problems-solving style, mindfulness, stress, anxiety, depression, and the Five Factor Model of Personality. We concluded that the SBS-13 is a significant contribution to the research on spiritual bypass and can be used in clinical settings as a screening tool and for future research.
Overcoming partitioning in large ad hoc networks using genetic algorithms

We deal in this paper with the important problem of partitioning in ad hoc networks. In our approach, we assume that some devices might have other communication interfaces rather than Wi-Fi and/or Bluetooth allowing to connect remote devices (e.g., technologies such as GPRS or HSDPA). This would allow us to build hybrid networks for overcoming the network partitioning. Hence, the problem considered in this work is to establish remote links between devices (called bypass links) in order to maximize the QoS of the network by optimizing its properties to make it small world. Additionally, the number of this kind of links in the network should be minimized as well, since we consider that not all the devices have these communication capabilities, or it could be a requirement to minimize the use of the long range network (for example, in the case its use supposes some cost). We face the problem with four different GAs (both parallel and sequential) and compare their behaviors on six different network instances. All the algorithms were tested with a new encoding of the problem, which is demonstrated to provide more accurate results than the previously existing one.
Anatomically Plausible Surface Alignment and Reconstruction

With the increasing clinical use of 3D surface scanners, there is a need for accurate and reliable algorithms that can produce anatomically plausible surfaces. In this paper, a combined method for surface alignment and reconstruction is proposed. It is based on an implicit surface representation combined with a Markov Random Field regularisation method. Conceptually, the method maintains an implicit ideal description of the sought surface. This implicit surface is iteratively updated by realigning the input point sets and Markov Random Field regularisation. The regularisation is based on a prior energy that has earlier proved to be particularly well suited for human surface scans. The method has been tested on full cranial scans of ten test subjects and on several scans of the outer human ear.
A Solution of Combining Several Classifiers for Face Recognition

past years, numerous face recognition algorithms have been proposed by researchers. However, there is no evidence that shows one specific proposed method is the best under all circumstances. So, a combination of several methods can be a good approach. Committee machine structures, which were introduced in the machine learning community, show some ways to combine different methods in a single framework. A committee machine structure makes decision according to its components. In the previous face recognition methods with committee machines, only the information which is extracted from test phase is used for combining classifiers. In this paper, in addition to the information in test phase, training phase information is used for combining classifiers. For this purpose, we introduce a new unit which is called " Region Finder ". This unit is attached to each classifier in a committee machine structure and is learned based on train phase information. A region finder determines its classifier recognition power in the classifier feature space. We applied our idea to a structure of five well-known classifiers, PCA, ICA, LDA, SVM and neural networks which are implemented for face recognition. Comparative experimental results of our committee machine with different algorithms and the structure without region finder units, demonstrate that the proposed system achieves improved accuracy.
Downlink resource allocation and pricing for wireless networks

This paper considers resource allocation and pricing for the downlink of a wireless network. We describe a model that applies to either a time-slotted system (e.g. Qualcomm's HDR proposal) or a CDMA system; the main feature of this model is that the channel quality varies across the users. We study using a pricing scheme for the allocation of radio resources. We show that to maximize revenue in such a system, the base station should allocate resources in a discriminatory manner, where different users are charged different prices based in part on their channel quality. However, optimally allocating resources in this way is shown to require knowledge about each user's utility function. We consider a suboptimal scheme which does not require knowledge of the users' utility functions, and show that this scheme is asymptotically optimal, in the limit of large demand. Moreover, such a scheme is shown to maximize social welfare. We also consider a heuristic scheme for the case of small demand, which does not require perfect knowledge about the users' utility functions. We provide numerical results that illustrate the performance of this heuristic.
Direct-sequence spread-spectrum with multiuser detection for peer to peer packet radio

The performance of direct-sequence spread-spectrum (DS/SS) in packet radio networks suffers from the near-far problem. This can be mitigated by the use of multiuser receivers. This paper introduces a model for peer to peer communications using a simple parallel interference cancellation (PIC) technique, which requires cancellation of only a few dominant interferers. The system performance is evaluated for various spatial arrangements of users, and for different loading conditions. Simulation results are provided for PIC.
Automatic Recognition of Surgical Motions Using Statistical Modeling for Capturing Variability

The ability to accurately recognize elementary surgical gestures is a stepping stone to automated surgical assessment and surgical training. However, as the pool of subjects increases, variation in surgical techniques and unanticipated motion increases the challenge of creating robust statistical models of gestures. This paper examines the applicability of advanced modeling techniques from automated speech recognition to the problem of increasing variability in surgical motions. In particular, we demonstrate the effectiveness of automatically bootstrapped user-adaptive models on diverse data acquired from the da Vinci surgical robot.
Review of the Literature on Time-Optimal Control of Robotic Manipulators

A task that robotic manipulators most frequently perform is motion between specified points in the working space. It is therefore important that these motions are efficient. The presence of the obstacles and other requirements of the task often require that the path is specified in advance. Robot actuators cannot generate unlimited forces/torques so it is reasonable to ask how to traverse the prespecified path in minimum time so that the limits on the actuator torques are not violated. It can be shown that the motion which requires least time to traverse a path requires at least one actuator to operate on the boundary (maximum or minimum). Furthermore, if the path is parameterized, the equations describing the robot dynamics can be rewritten as functions of the path parameter and its first and second derivatives. In general, the actuator bounds will be transformed into the bounds on the acceleration along the path. These bounds will be functions of the velocity and position. It is possible to demonstrate that the optimal motion will be almost always bang-bang in acceleration. The task of finding the optimal torques thus reduces to finding the instants at which the acceleration will switch between the boundaries. An algorithm for finding the time optimal motion along prespecified paths that explores this idea will be presented. It will be shown that so called singular arcs exist on which the algorithm will fail. Modification of the algorithm for such situations will be presented. Also, some properties of the solutions of the more general problem when the path is not known will be discussed. Lie-algebraic techniques will be shown to be a convenient tool for the study of such problems. Comments University of Pennsylvania Institute for Research in Cognitive Science Technical Report No. IRCS-94-34. This technical report is available at ScholarlyCommons: http://repository.upenn. edu/ircs_reports/179
Social workers’ attitudes toward human rights in a sample from Taiwan

The human rights concept is that everyone is entitled to enjoy those rights inherent to being human, without distinction. However, should human rights be considered a self-evident value for the social work profession? This study was to explore how social workers in Taiwan perceive the human rights concept. Responses from 276 social worker participants were analyzed by using a self-administered questionnaire. This study showed that social workers had a general knowledge of human rights. Receiving human rights educational training and engaging in social protests were important variables in increasing human rights awareness for social work practitioners.
An Architecture of Distributed Intrusion Detection System Based on SoftMan Platform

Soft Man is an intelligence software entity which is the human’s extension and expansion in the virtual world. For Soft Man entity run in the virtual network, the Soft Man Platform implements a series of services and mechanisms by simulating the model of human society. Using the platform which is the loosely organizational model to build a Soft Man-oriented Distributed Intrusion Detection System(SMDIDS), not only can effectively solve the problem of single point failure, but can also easy to build a flexibility architecture with none centralized control. And with the technology of multi-level migration and humanized characteristic of the Soft Man, the SMDIDS provide a novel method for implementation of network security.
Effect of mutual interference and channel estimation error on outage performance of reactive relay selection in unlicensed systems

This study addresses the effects of channel estimation error and mutual interference between licensed and unlicensed systems on outage performance of reactive relay selection in unlicensed systems over independent non-identical (i.n.i) Rayleigh fading channels and under both the maximum transmit power constraint and primary outage constraint. Toward this end, power allocation for unlicensed users is first recommended to satisfy both constraints and account for channel estimation error and mutual interference. Then, we derive an exact closed-form outage probability representation for unlicensed systems to quickly evaluate this effect in key operation parameters. Various results corroborate the derived expressions and provide useful insights into system performance.
Sampling-based approaches to accelerate network-on-chip simulation

Architectural complexity continues to grow as we consider the large design space of multiple cores, cache architectures, networks-on-chip (NoC) and memory controllers. Simulators are growing in complexity to reflect these system components. However, many full-system simulators fail to utilize the underlying hardware resources such as multiple cores; consequently, simulation times have grown significantly. Long turnaround times limit the range and depth of design space exploration. Communication has emerged as a first class design consideration and has led to significant research into NoCs. NoC is yet another component of the architecture that must be faithfully modeled in simulation. Here, we focus on accelerating NoC simulation through the use of sampling techniques. We propose NoCLabs and NoCPoint, two sampling methodologies utilizing statistical sampling theory and traffic phase behavior, respectively. Experimental results show that NoCLabs and NoCPoint estimate NoC performance with an average error of 7% while achieving one order of magnitude speedup.
Approach comparing external and internal methods for analysing group dynamic 1 1 An approach to comparing external and internal methods for analysing group dynamic

Running head: Approach comparing external and internal methods for analysing group dynamic 2 2 Abstract Beginning with the question, can a multi-methodology explore the nature of group work from both the inside out (group participant self-analysis) and the outside in (facilitator observed analysis), this paper presents the results of a statistical analysis comparing two different approaches to assessing group function; SYMLOG (A SYstem for the Multiple Level Observation of Groups) and BECM (Being, Engaging, Contextualising and Managing). SYMLOG is a quantitative internal assessment of group function made by members of the group, while BECM is qualitative external assessment made by an outsider observing the groups. Together, it is argued, they provide a unique, triangulated assessment of the group dynamic. By employing a 'best subsets' linear regression technique it was found that some of the 26 characteristics of SYMLOG are related to BECM scoring (adjusted R 2 = 0.82). The paper discusses the reasons for this and the repercussions for such blending of approaches to understanding group dynamic. The paper ends by discussing the relative advantages and disadvantages of the two approaches and potential for further hybridising of them in blended group dynamic approaches.