Project-based strategic management education: A client perspective on key challenges

This paper explores the benefits of project-based learning from the small business client perspective. The reflections of a sample of small businesses were collected through a feedback survey after participating in a semester-long project-based learning process developed for the Strategic Management curriculum in the College of Business at Western Carolina University (WCU). The clients that participated in projects are primarily local and regional businesses in Western North Carolina; they were sourced through the Small Business Centers (SBC) located at the area community colleges and the Small Business and Technology Development Center (SBTDC) located at WCU. Most participating organizations are existing small businesses or start-ups with a high probability and capacity for growth that will enhance the economic development of the region. Literature review of both small business and project-based pedagogy challenges demonstrated the potential for co-creation of value. This study laid out the steps we took to organize a project-based Strategic Management pedagogy. Our analysis of both close- and open-ended client feedback revealed four key success factor themes for developing a mutually beneficial project-based pedagogy: communication and interaction, project organization and student preparation, quality of work, and co-creation of value; the specific priority actions for each theme are detailed in the paper

Visual Pigments and Light Detection in the Eye

Most forms of animal vision begin with light absorption by visual pigments in the eye. A typical visual pigment consists of a G protein-coupled receptor protein – opsin – covalently conjugated to a chromophore. Sub-families of opsins show distinctive physicochemical properties and cellular expressions, often attuned to the specific visual functions that they serve. Here, we examined a number of molecular and functional features of three sub-families of opsins. We found that: (1) an active molecule of rhodopsin (a ciliary opsin expressed in rod photoreceptors for dim-light vision) amplifies the light signal by activating about 20-30 transducin molecules at the peak of the current response to single photon-absorption. (2) the thermal activation of native and some mutant rhodopsin and cone pigments (ciliary opsins in cone photoreceptors for color vision) in the dark is indeed an isomerization event, the rate of which can be quantitatively predicted by multi-vibrational-mode statistical mechanics. (3) melanopsin, a rhabdomeric opsin that underlies the intrinsic photosensitivity of a subgroup of retinal ganglion cells and is responsible for diverse non-image-forming visual functions in mammals, is also expressed in some thick, myelinated neuronal processes in the rat iris that possibly originate from the trigeminal ganglia. (4) neuropsin (OPN5), a previous orphan opsin, mediates the photoentrainment of the local circadian rhythm in the mammalian retina and cornea

Equipping Federated Graph Neural Networks with Structure-aware Group Fairness

Graph Neural Networks (GNNs) have been widely used for various types of graph data processing and analytical tasks in different domains. Training GNNs over centralized graph data can be infeasible due to privacy concerns and regulatory restrictions. Thus, federated learning (FL) becomes a trending solution to address this challenge in a distributed learning paradigm. However, as GNNs may inherit historical bias from training data and lead to discriminatory predictions, the bias of local models can be easily propagated to the global model in distributed settings. This poses a new challenge in mitigating bias in federated GNNs. To address this challenge, we propose $\text{F}^2$GNN, a Fair Federated Graph Neural Network, that enhances group fairness of federated GNNs. As bias can be sourced from both data and learning algorithms, $\text{F}^2$GNN aims to mitigate both types of bias under federated settings. First, we provide theoretical insights on the connection between data bias in a training graph and statistical fairness metrics of the trained GNN models. Based on the theoretical analysis, we design $\text{F}^2$GNN which contains two key components: a fairness-aware local model update scheme that enhances group fairness of the local models on the client side, and a fairness-weighted global model update scheme that takes both data bias and fairness metrics of local models into consideration in the aggregation process. We evaluate $\text{F}^2$GNN empirically versus a number of baseline methods, and demonstrate that $\text{F}^2$GNN outperforms these baselines in terms of both fairness and model accuracy

Carbenoxolone does not cross the blood brain barrier: an HPLC study

BACKGROUND: Carbenoxolone (CBX) is a widely used gap junctional blocker. Considering several reports indicating that transient gap junctional blockade could be a favourable intervention following injuries to central nervous tissue, and some current enthusiasm in studies using systemic injections of CBX, it is imperative to consider the penetration of CBX into central nervous tissue after systemic administrations. So far, only very indirect evidence suggests that CBX penetrates into the central nervous system after systemic administrations. We thus determined the amounts of CBX present in the blood and the cerebrospinal fluid of rats after intraperitoneal administration, using high performance liquid chromatography RESULTS: CBX was found in the blood of the animals, up to 90 minutes post-injection. However, the cerebrospinal fluid concentration of CBX was negligible. CONCLUSION: Thus, we conclude that, most likely, CBX does not penetrate the blood brain barrier and therefore recommend careful consideration in the manner of administration, when a central effect is desired

Long-Range Ordered Carbon Clusters: A Crystalline Material with Amorphous Building Blocks

Solid-state materials can be categorized by their structures into crystalline (having periodic translation symmetry), amorphous (no periodic and orientational symmetry), and quasi-crystalline (having orientational but not periodic translation symmetry) phases. Hybridization of crystalline and amorphous structures at the atomic level has not been experimentally observed. We report the discovery of a long-range ordered material constructed from units of amorphous carbon clusters that was synthesized by compressing solvated fullerenes. Using x-ray diffraction, Raman spectroscopy, and quantum molecular dynamics simulation, we observed that, although carbon-60 cages were crushed and became amorphous, the solvent molecules remained intact, playing a crucial role in maintaining the long-range periodicity. Once formed, the high-pressure phase is quenchable back to ambient conditions and is ultra-incompressible, with the ability to indent diamond

A new exponentiated beta burr type X distribution : model, theory, and applications

In recent years, many attempts have been carried out to develop the Burr type X distribution, which is widely used in fitting lifetime data. These extended Burr type X distributions can model the hazard function in decreasing, increasing and bathtub shapes, except for unimodal. Hence, this paper aims to introduce a new continuous distribution, namely exponentiated beta Burr type X distribution, which provides greater flexibility in order to overcome the deficiency of the existing extended Burr type X distributions. We first present its density and cumulative function expressions. It is then followed by the mathematical properties of this new distribution, which include its limit behaviour, quantile function, moment, moment generating function, and order statistics. We use maximum likelihood approach to estimate the parameters and their performance is assessed via a simulation study with varying parameter values and sample sizes. Lastly, we use two real data sets to illustrate the performance and flexibility of the proposed distribution. The results show that the proposed distribution gives better fits in modelling lifetime data compared to its sub-models and some extended Burr type X distributions. Besides, it is very competitive and can be used as an alternative model to some nonnested models. In summary, the proposed distribution is very flexible and able to model various shaped hazard functions, including the increasing, decreasing, bathtub, and unimodal

Exponentiated Weibull Burr Type X Distribution’s Properties and Its Applications

This study proposes a new distribution called exponentiated Weibull Burr type X distribution which provides greater flexibility in fitting the survival data. We derive several statistical properties of the proposed distribution, which consist of the quantile function, moment, order statistics, and Renyi entropy. We use maximum likelihood approach to estimate the proposed distribution’s parameters. Simulation study is then conducted with varying samples sizes and parameter values for examining the performance of the suggested distribution. Lastly, real data are used to illustrate the flexibility and performance of the proposed distribution, its sub-models, and some extension of Burr type X distribution. The results reveal that the suggested distribution yields a better model fit in comparison with other competing models. In conclusion, the proposed distribution able to model a wide range of survival data, including data with decreasing, increasing, bathtub, and unimodal hazard functions. Perhaps it may perform better than its sub-models in fitting the survival data

Exponentiated Weibull Burr Type X Distribution’s Properties and Its Applications

This study proposes a new distribution called exponentiated Weibull Burr type X distribution which provides greater flexibility in fitting the survival data. We derive several statistical properties of the proposed distribution, which consist of the quantile function, moment, order statistics, and Renyi entropy. We use maximum likelihood approach to estimate the proposed distribution’s parameters. Simulation study is then conducted with varying samples sizes and parameter values for examining the performance of the suggested distribution. Lastly, real data are used to illustrate the flexibility and performance of the proposed distribution, its sub-models, and some extension of Burr type X distribution. The results reveal that the suggested distribution yields a better model fit in comparison with other competing models. In conclusion, the proposed distribution able to model a wide range of survival data, including data with decreasing, increasing, bathtub, and unimodal hazard functions. Perhaps it may perform better than its sub-models in fitting the survival data

A Model to Induce Low Temperature Trauma for in vitro Astrogliosis Study*

Astrogliosis is an inevitable and rapid response of astrocytes to physical, chemical and pathological injuries. To study astrogliosis, we developed a reproducible in vitro model in which low temperature injury to cultured astrocytes could be induced by placing the culture dish onto a copper pipe pre-cooled by liquid nitrogen. Using this model, the relationship between the temperature decline and the severity of cellular damage was analyzed. An increase in the expression of some known injury-related proteins, such as glial fibrillary acidic protein (GFAP), immediate early response genes (IEGs), and heat shock proteins 70 (HSP70), was demonstrated in astrocytes after low temperature trauma. With the use of this low temperature trauma model, the flexibility in the temperature control and injury area may allow researchers to evaluate cryotherapy and cryosurgery, which could be applicable to future development of quality health care