Psychopathology of Dementia: Psychology’s Pivotal Role

Biology does not completely explain dementia. We can neither predict nor confirm a diagnosis of dementia based purely on its biology. Recent studies looking at prevention using social interventions hold better promise for ameliorating the disease. Yet, we do not have a major theory to explain these outcomes without resorting to biology. By understanding that there are mediating and moderating psychological factors promoting dementia, we take a broader view of the disease than a simple binary approach. Psychology plays a vital role in this clinical disease, in how cognition affects dementia. The presumption is that all of cognition: perception, orientation, novelty, attention, the application of knowledge (praxis), calculation, language, abstract thinking, and memory can affect and bring about dementia. It is not dementia that causes cognitive decline but cognitive decline that causes dementia. The psychopathology of dementia can initiate dementia, moderate it by enhancing or retarding the progression of the disease or mediate the disease by acting as a confirmatory process. The tipping point expressed by apathy and depression heralds a change in cognition. The psychopathology of dementia is important in understanding the etiology of dementia as it holds the most promising avenue for curing some dementias.

Towards real-time PGS range monitoring in proton therapy of prostate cancer

Proton therapy of prostate cancer (PCPT) was linked with increased levels of gastrointestinal toxicity in its early use compared to intensity-modulated radiation therapy (IMRT). The higher radiation dose to the rectum by proton beams is mainly due to anatomical variations. Here, we demonstrate an approach to monitor rectal radiation exposure in PCPT based on prompt gamma spectroscopy (PGS). Endorectal balloons (ERBs) are used to stabilize prostate movement during radiotherapy. These ERBs are usually filled with water. However, other water solutions containing elements with higher atomic numbers, such as silicon, may enable the use of PGS to monitor the radiation exposure of the rectum. Protons hitting silicon atoms emit prompt gamma rays with a specific energy of 1.78 MeV, which can be used to monitor whether the ERB is being hit. In a binary approach, we search the silicon energy peaks for every irradiated prostate region. We demonstrate this technique for both single-spot irradiation and real treatment plans. Real-time feedback based on the ERB being hit column-wise is feasible and would allow clinicians to decide whether to adapt or continue treatment. This technique may be extended to other cancer types and organs at risk, such as the oesophagus.

Does it pay to act feminine? A cross-cultural study of gender stereotype endorsement and cognitive legitimacy in the evaluation of new ventures

PurposeDoes gender stereotype endorsement play a role in the customer's cognitive evaluation of new ventures owned by women entrepreneurs? The authors’ cross-cultural study integrates literature on gender stereotype endorsement and cognitive legitimacy to address this research question.Design/methodology/approachThe authors use a two-study experimental design and analyze our results by cultural context to test our hypotheses: one drawn from college students in Iran and one from working professionals in the United States.FindingsThe authors’ comparative results suggest that the evaluation of feminine versus masculine characteristics of women entrepreneurs varies depending on the evaluator's (in this case the customer's) endorsement of gender stereotypes and the cultural context. Specifically, the authors found that a new venture owned by a woman entrepreneur who displays feminine characteristics is perceived as more legitimate when the customer endorses feminine stereotypes, regardless of the country.Research limitations/implicationsThe authors’ research contributes to the literature on cognitive legitimacy and women's entrepreneurship by unveiling the cultural conditions and factors that allow women entrepreneurs to benefit from acting in a stereotypically feminine way. The authors use a binary approach to gender. Future research should extend our findings to also include a non-binary approach.Originality/valueThis study contributes to women's entrepreneurship research by unraveling the implications of gender stereotype endorsement, legitimacy and culture in customer evaluation of ventures owned by women.

High speed data encryption technique with optimized memory based RSA algorithm for communications

Purpose The privacy of the information is a major challenge in the communication process. In the present modern generation, the cryptography plays a vital role in providing security for data, such as text, images and video while transmitting from source to destination through internet or intranet. The Rivest-Shamir-Adleman (RSA) is an asymmetric key cryptographic system, where the security of the method works on the strength of the key. Design/methodology/approach In an asymmetric key crypto system, a pair of keys is generated one public key for encryption and one private key for decryption. The major challenge of implementing the RSA is the power function which becomes tedious and time consuming as the exponential value increases. The Chinese remainder theorem proves to be the best for data encryption when it comes to execution time of the algorithm. The proposed novel RSA algorithm with lookup table (LUT) is an extension to the Chinese remainder algorithm, which works better for image and video in terms of time complexity. Findings This paper presents a LUT approach for implementing the RSA with a minimal processing time. The proposed algorithm was compared with the standard algorithms like, Chinese remainder theorem, binary approach and squared multiplication approach. As the size of the exponent value increases, the proposed method shows better performance compared to other standard methods. Originality/value This paper presents a LUT approach for implementing the RSA with a minimal processing time. The proposed algorithm was compared with the standard algorithms like, Chinese remainder theorem, binary approach and squared multiplication approach. As the size of the exponent value increases, the proposed method shows better performance compared to other standard methods.

A novel binary k-mer approach for classification of coding and non-coding RNAs across diverse species

Classification among coding (CDS) and non-coding RNA (ncRNA) sequences is a challenge and several machine learning models have been developed for the same. Since the frequency of curated coding sequences is many-folds as compared to that of the ncRNAs, we devised a novel approach to work with the complete datasets from fifteen diverse species. In our proposed novel binary approach, we replaced all the A,T with 0 and G,C with 1 to obtain a binary form of coding and ncRNAs. The k-mer analysis of these binary sequences revealed that the frequency of binary patterns among the coding and ncRNAs can be used as features to distinguish among them. Using insights from these distinguishing frequencies, we used k-nearest neighbour classifier to classify among them. Our strategy is not only time-efficient but leads to significantly increased performance metrics including Matthews correlation coefficient (MCC) for some species like P. paniscus, M. mulatta, M. lucifugus, G. gallus, C. japonica, C. abingdonii, A. carolinensis, D. melanogaster and C. elegans when compared with the conventional ATGC approach. Additionally, we also show that the values of MCC obtained for diverse species tested on the model based on H. sapiens correlated with the geological evolutionary timeline thereby further strengthening our approach. Therefore, we propose that CDS and ncRNAs can be efficiently classified using 2-character frequency as compared to 4-character frequency of ATGC approach. Thus, our highly efficient binary approach can replace the more complex ATGC approach successfully.

Using top-down gating to optimally balance shared versus separated task representations

Human adaptive behavior requires continually learning and performing a wide variety of tasks, often with very little practice. To accomplish this, it is crucial to separate neural representations of different tasks in order to avoid interference. At the same time, sharing neural representations supports generalization and allows faster learning. Therefore, a crucial challenge is to find an optimal balance between shared versus separated representations. Typically, models of human cognition employ top-down gating signals to separate task representations, but there exist surprisingly little systematic computational investigations of how such gating is best implemented. We identify and systematically evaluate two crucial features of gating signals. First, top-down input can be processed in an additive or multiplicative manner. Second, the gating signals can be adaptive (learned) or non-adaptive (random). We cross these two features, resulting in four gating models which are tested on a variety of input datasets and tasks with different degrees of stimulus-action mapping overlap. The multiplicative adaptive gating model outperforms all other models in terms of accuracy. Moreover, this model develops hidden units that optimally share representations between tasks. Specifically, different than the binary approach of currently popular latent state models, it exploits partial overlap between tasks.

Not additive, not defined: mutual constitution in feminist intersectional studies

The term ‘mutual constitution’ appears with regularity in scholarship on intersectionality, but what does it mean? We could not easily answer this question in the usual way – by reading books and articles about it – because the term has not received direct, widespread or sustained engagement in feminist theory. This led us to analyse a wide range of feminist scholarship – the entire set of 379 articles in women’s studies journals that consider both intersectionality and mutual constitution – to determine whether there are patterns and commonalities in the ways this important theoretical term is used. Our analysis reveals that while there is widespread agreement that mutual constitution does not allow for an additive or binary approach, this is the only major point of shared understanding of this term. Scholars disagree over whether mutual constitution is, in fact, the same thing as intersectionality, and in practice, clusters of disciplines use the term with different norms and levels of precision. Because of the explanatory potential of this term in intersectional theory, we recommend on the basis of our analysis that social scientists reconsider the convention of asserting that entities such as race, class and gender are mutually constituted and borrow the methodological tools from feminist historians, literary critics and other humanists that would allow for a genuine determination and demonstration of when entities are mutually constituted.