bluuebunny/crossref_metadata_2025_split huggingface dataset:
Graded multidimensional clinical and radiological variation in patients with Alzheimer’s disease and posterior cortical atrophy
Authors: Ingram Ruth U. , Ocal Dilek , Halai Ajay D. , Pobric Gorana , Cash David , Crutch Sebastian J. , Yong Keir X.X. , Lambon Ralph Matthew A. 
Published: February 2023

AbstractBackground and ObjectivesAlzheimer’s disease spans heterogeneous typical and atypical phenotypes. Posterior cortical atrophy is one striking example, characterised by prominent impairment in visual and other posterior functions in contrast to typical, amnestic Alzheimer’s disease. The primary study objective was to establish how the similarities and differences of cognition and brain volumes within Alzheimer’s disease and posterior cortical atrophy (and by extension other Alzheimer’s disease variants), can be conceptualised as systematic variations across a transdiagnostic, graded multidimensional space.MethodsThis was a cross-sectional, single-center, observational, cohort study performed at the National Hospital for Neurology & Neurosurgery, London, UK. Data were collected from a cohort of PCA and AD patients, matched for age, disease duration and MMSE scores. There were two sets of outcome measures: (1) scores on a neuropsychological battery containing 22 tests spanning visuoperceptual and visuospatial processing, episodic memory, language, executive functions, calculation, and visuospatial processing; and (2) measures extracted from high-resolution T1-weighted volumetric MRI scans. Principal component analysis was used to extract the transdiagnostic dimensions of phenotypical variation from the detailed neuropsychological data. Voxel-based morphometry was used to examine associations between the PCA-derived clinical phenotypes and the structural measures.ResultsWe enrolled 93 PCA participants (mean: age = 59.9 yrs, MMSE = 21.2; 59/93 female) and 58 AD participants (mean: age = 57.1 yrs, MMSE = 19.7; 22/58 female). The principal component analysis for posterior cortical atrophy (sample adequacy confirmed: Kaiser-Meyer-Olkin = 0.865) extracted three dimensions accounting for 61.0% of variance in patients’ performance, reflecting general cognitive impairment, visuoperceptual deficits and visuospatial impairments. Plotting Alzheimer’s disease cases into the posterior cortical atrophy-derived multidimensional space, and vice versa, revealed graded, overlapping variations between cases along these dimensions, with no evidence for categorical-like patient clustering. Likewise, the relationship between brain volumes and scores on the extracted dimensions was overlapping for posterior cortical atrophy and Alzheimer’s disease cases.DiscussionThese results provide evidence supporting a reconceptualization of clinical and radiological variation in these heterogenous Alzheimer’s disease phenotypes as being along shared phenotypic continua spanning posterior cortical atrophy and Alzheimer’s disease, arising from systematic graded variations within a transdiagnostic, multidimensional neurocognitive geometry.
Metabolic modeling of sex-specific tissue predicts mechanisms of differences in toxicological responses
Authors: Moore Connor J. , Holstege Christopher P. , Papin Jason A. 
Published: February 2023

AbstractMale subjects in animal and human studies are disproportionately used for toxicological testing. This discrepancy is evidenced in clinical medicine where females are more likely than males to experience liver-related adverse events in response to xenobiotics. While previous work has shown gene expression differences between the sexes, there is a lack of systems-level approaches to understand the direct clinical impact effect of these differences. Here, we integrate gene expression data with metabolic network models to characterize the impact of transcriptional changes of metabolic genes in the context of sex differences and drug treatment. We used Tasks Inferred from Differential Expression (TIDEs), a reaction-centric approach to analyzing differences in gene expression, to discover that androgen, ether lipid, glucocorticoid, tryptophan, and xenobiotic metabolism have more activity in the male liver, and serotonin, melatonin, pentose, glucuronate, and vitamin A metabolism have more activity in the female liver. When TIDEs is used to compare expression differences in treated and untreated hepatocytes, we see little response in those sex-altered subsystems, and the largest differences are in subsystems related to lipid metabolism. Finally, using sex-specific transcriptomic data, we create individual and averaged male and female liver models and find differences in the import of bile acids and salts. This result suggests that the sexually dimorphic behavior of the liver may be caused by differences in enterohepatic recirculation, and we suggest an investigation into sex-specific microbiome composition as an avenue of further research.Author SummaryMale-bias in clinical testing of drugs has led to a disproportionate number of hepatotoxic events in women. Previous works use gene-by-gene differences in biological sex to explain this discrepancy, but there is little focus on the systematic interactions of these differences. To this end, we use a combination of gene expression data and metabolic modeling to compare metabolic activity between the male and female liver and treated and untreated hepatocytes. We find several subsystems with differential activity in each sex; however, when comparing these subsystems with those pathways altered by hepatotoxic agents, we find little overlap. To explore these differences on a reaction-by-reaction basis, we use the same sex-specific transcriptomic data to contextualize the previously published Human1 human cell metabolic model. In these models we find a difference in flux for the import of bile acids and salts, suggesting a potential difference in enterohepatic circulation. These findings can help guide future drug design, toxicological testing, and sex-specific research to better account for the entire human population.
CircSSNN: circRNA-binding site prediction via sequence self-attention neural networks with pre-normalization
Authors: Cao Chao , Yang Shuhong , Li Mengli , Li Chungui 
Published: February 2023

AbstractCircular RNAs (circRNAs) play a significant role in some diseases by acting as transcription templates. Therefore, analyzing the interaction mechanism between circRNA and RNA-binding proteins (RBPs) has far-reaching implications for the prevention and treatment of diseases. Existing models for circRNA-RBP identification most adopt CNN, RNN, or their variants as feature extractors. Most of them have drawbacks such as poor parallelism, insufficient stability, and inability to capture long-term dependence. To address these issues, we designed a Seq_transformer module to extract deep semantic features and then propose a CircRNA-RBP identification model based on Sequence Self-attention with Pre-normalization. We test it on 37 circRNA datasets and 31 linear RNA datasets using the same set of hyperparameters, and the overall performance of the proposed model is highly competitive and, in some cases, significantly out-performs state-of-the-art methods. The experimental results indicate that the proposed model is scalable, transformable, and can be applied to a wide range of applications without the need for task-oriented fine-tuning of parameters. The code is available athttps://github.com/cc646201081/CircSSNN.Author summaryIn this paper, we propose a new method completely using the self-attention mechanism to capture deep semantic features of RNA sequences. On this basis, we construct a CircSSNN model for the cirRNA-RBP identification. The proposed model constructs a feature scheme by fusing circRNA sequence representations with statistical distributions, static local context, and dynamic global context. With a stable and efficient network architecture, the distance between any two positions in a sequence is reduced to a constant, so CircSSNN can quickly capture the long-term dependence and extract the deep semantic features. Experiments on 37 circRNA datasets show that the proposed model has overall advantages in stability, parallelism, and prediction performance. Keeping the network structure and hyperparameters unchanged, we directly apply CircSSNN to linRNA datasets. The favorable results show that CircSSNN can be transformed simply and efficiently without task-oriented tuning. In conclusion, CircSSNN can serve as an appealing circRNA-RBP identification tool with good identification performance, excellent scalability, and wide application scope, which is expected to reduce the professional threshold required for hyperparameter tuning in bioinformatics analysis.
Investigation of the strength of forged rivet joints made with different bucking bar gaps
Authors: Soylak Mustafa , Erturun Veysel 
Published: February 2023

Purpose
The purpose of this study is to examine the effect of the rivet heads formed on the rivet strength by an experimental study if the bucking bar used in the forged rivet application includes gaps with different angles.

Design/methodology/approach
0.81 (0.032”) mm thick 2024 T3 sheets were used for the rivet joints. AD 2117 T4 forged rivets with a diameter of 3.2 mm (0.125″, 1/8″) are used for the joints. The special bucking bars (sidewall intersection angles of flat, 40°, 60° and 80°) were manufactured for the riveting process. To determine the mechanical properties of the prepared samples, cross-tension and tensile-shear tests were performed on a universal tensile testing machine.

Findings
As a result of the tensile-shear tests and cross-tensile, use of an 80 degrees bucking bar instead of rivets with a flat bucking bar increases the strength of the joint by approximately 20%. There is no systematic change in elongation. The results of tensile-shear and cross-tensile tests showed that forging rivets by special bucking bars have a significant effect on joint strength.

Originality/value
Increase in strength will require the use of thinner sheet metal and smaller rivets to achieve the same strength. This will reduce the weight of the aircraft. Weight reduction also means less fuel consumption and more economical flight. This increase in strength is a very important scientific achievement.
A study on the competitive dissemination of disinformation and knowledge on social media
Authors: Wu YiShu , Wang Dandan , Ma Feicheng 
Published: February 2023

PurposeThe purpose of this study is to explore the evolutionary path and stable strategy for the competitive dissemination between disinformation and knowledge on social media to provide effective solutions to curb the dissemination of disinformation and promote the spread of knowledge.Design/methodology/approachBased on the social capital (SC) theory, the benefit matrix is constructed and an evolutional game model is established in this paper. Through model solving and Matrix Laboratory (MATLAB) simulation, the factors that influence disinformation-believing users (DUs) and knowledge-believing users (KUs) to choose different strategies are analyzed.FindingsThe initial dissemination willingness, the disinformation infection probability, the knowledge infection probability and the knowledge penetration probability are proved to be crucial factors influencing the game equilibrium in the competitive dissemination process of disinformation and knowledge. Moreover, some countermeasures and recommendations for the governance of disinformation are proposed.Originality/valueCurrently most research interest lies in the disinformation dissemination model but ignores the interaction between disinformation and knowledge in the diffusion process. This study reveals the dynamic mechanism of social media users disseminating disinformation and knowledge and is expected to promote the formation of cleaner cyberspace.
Understanding TMS and knowledge transfer in the social media mobile App context
Authors: Yan Yalan , Xin Siyu , Zha Xianjin 
Published: February 2023

PurposeKnowledge transfer which refers to the communication of knowledge from a source so that it is learned and applied by a recipient has long been a challenge for knowledge management. The purpose of this study is to understand influencing factors of transactive memory system (TMS) and knowledge transfer.Design/methodology/approachDrawing on the theories of communication visibility, social distance and flow, this study develops a research model. Then, data are collected from users of the social media mobile App. Partial least squares-structural equation modeling (PLS-SEM) is employed to analyze data.FindingsTMS is a valid second-order construct in the social media mobile app context, which is more reflected by credibility. Meanwhile, communication visibility and social distance each have positive effects on TMS which further has a positive effect on knowledge transfer. Flow has a positive effect on knowledge transfer.Practical implicationsDevelopers of the mobile App should carefully consider the role of information and communication technology (ICT) in supporting TMS and knowledge transfer. They should consider recommendation algorithm so that the benefit of communication visibility can be retained. They should design the feature to classify users based on similarity so as to stimulate users' feeling of close social distance. They should keep on improving features based on users' holistic experience.Originality/valueThis study incorporates the perspectives of communication visibility, social distance and flow to understand TMS and knowledge transfer, presenting a new lens for research.
The fractal active low-pass filter within the local fractional derivative on the Cantor set
Authors: Wang Kang-Jia 
Published: February 2023

Purpose
The purpose of this paper is to derive a new fractal active low-pass filter (LPF) within the local fractional derivative (LFD) calculus on the Cantor set (CS).

Design/methodology/approach
To the best of the author’s knowledge, a new fractal active LPF within the LFD on the CS is proposed for the first time in this work. By defining the nondifferentiable (ND) lumped elements on the fractal set, the author successfully extracted its ND transfer function by applying the local fractional Laplace transform. The properties of the ND transfer function on the CS are elaborated in detail.

Findings
The comparative results between the fractal active LPF (for γ = ln2/ln3) and the classic one (for γ = 1) on the amplitude–frequency and phase–frequency characteristics show that the proposed method is correct and effective, and is expected to shed light on the theory study of the fractal electrical systems.

Originality/value
To the best of the author’s knowledge, the fractal active LPF within the LFD calculus on the CS is proposed for the first time in this study. The proposed method can be used to study the other problems in the fractal electrical systems, and is expected to shed a light on the theory study of the fractal electrical systems.
A sensor data mining process for identifying root causes associated with low yield in semiconductor manufacturing
Authors: Kim Eunji , An Jinwon , Cho Hyun-Chang , Cho Sungzoon , Lee Byeongeon 
Published: February 2023

PurposeThe purpose of this paper is to identify the root cause of low yield problems in the semiconductor manufacturing process using sensor data continuously collected from manufacturing equipment and describe the process environment in the equipment.Design/methodology/approachThis paper proposes a sensor data mining process based on the sequential modeling of random forests for low yield diagnosis. The process consists of sequential steps: problem definition, data preparation, excursion time and critical sensor identification, data visualization and root cause identification.FindingsA case study is conducted using real-world data collected from a semiconductor manufacturer in South Korea to demonstrate the effectiveness of the diagnosis process. The proposed model successfully identified the excursion time and critical sensors previously identified by domain engineers using costly manual examination.Originality/valueThe proposed procedure helps domain engineers narrow down the excursion time and critical sensors from the massive sensor data. The procedure's outcome is highly interpretable, informative and easy to visualize.
Project-based learning and pedagogies for virtual reality-aided green building education: case study on a university course
Authors: Hou Huiying (Cynthia) , Lai Joseph H.K. , Wu Hao 
Published: February 2023

Purpose
Green building education, an important aspect of sustainability in higher education, has rapidly expanded across the world. Yet, a bespoke pedagogical model integrating the essential elements of green building knowledge into a university course is lacking. To plug this deficiency, this study aims to develop an innovative pedagogical model that incorporates four types of teaching activities, namely, lecture, virtual reality (VR)-aided site visit, physical site visit and practicum-based project.

Design/methodology/approach
Based on an extensive review of the relevant literature and course materials, a pedagogical model was constructed for application to the teaching and learning activities of a university’s hospitality and real-estate programme. Using a case study approach involving in-depth interviews with green building professionals and a workshop coupled with an online survey on building professionals, the model’s transformative effectiveness was evaluated.

Findings
The study finds that the pedagogical model was able to effectively equip students with the essential green building knowledge pertinent to the different stages of a building life cycle. Concerns about wider applications of the model, including barriers to implementation in other academic programmes and resources for updating the VR platform, were identified.

Originality/value
The VR-aided and project-based pedagogy model is novel and effective in delivering green building education. Future work, particularly expanding the VR platform to cover more green building cases, thereby allowing multiple case studies to be conducted, is recommended for illustrating further contributions and implications of the model.
Tax compliance of small and medium sized enterprises in Ghana
Authors: Nartey Edward 
Published: February 2023

PurposeTax compliance studies have been extensively conducted across various jurisdictions. However, only partial answers have so far been provided for the question: “Why do people pay tax?”. The aim of this study is to report tax compliance behavior from both the supply side (SMEs) and demand side (tax collecting authorities) in Ghana.Design/methodology/approachA survey of 233 responses comprising 169 SME managers and 64 tax officials of the Ghana Revenue Authority qualified for the study. Data were modelled using covariance-based structural equations modelling (AMOS Graphics version 23).FindingsIsomorphic forces and tax fairness have a positive impact on tax compliance. However, the impact of strategic response on tax compliance was insignificant, which suggests that, although SMEs in Ghana adopt different strategies to respond to institutional pressures, such strategies do not influence their tax compliance behavior.Research limitations/implicationsThis study investigates tax compliance behavior among SMEs using a survey design from only one developing country – Ghana. Based on a cross-sectional survey and the approach used to gather the sample data, assessing any changes over time may be impossible.Practical implicationsThe findings suggest that SMEs’ tax compliance behaviors are shaped by institutional pressures in terms of obeying tax laws and filling their tax returns in a consistent manner. Given that isomorphic forces and tax fairness are significant predictors of tax compliance, SME tax compliance can be improved if strong institutions are incorporated in the administration of taxes. The findings also support the logical thinking of tax fairness theory that the higher SMEs perceived the tax system to be fair, the more their compliance behavior is encouraged.Originality/valueThis study represents one of the few to provide preliminary empirical evidence on tax compliance from the supply side of taxation in a developing economy. Therefore, the findings have implications for taxpayers in Ghana.
Organisational identity development by entrepreneurial firms using social media: a process-based model
Authors: Badran Amer , Tanner Sean , Alton Dave 
Published: February 2023

Purpose
This paper aims to explore how entrepreneurs use social media (SM) to develop their organisational identity within business networks.

Design/methodology/approach
A single embedded case study was used comprising a case firm entrepreneur and eight connected network actors within an artisan food context in Ireland. Data was collected using an in-depth interview complemented with content analysis of networked firms’ Facebook posts (N = 1,652) over a three-year period.

Findings
This paper identifies four common network processes through which entrepreneurs can leverage SM to develop their organisational identity within networks. The processes are network relating, collaborating within networks, interacting with trends and connecting with community.

Research limitations/implications
Findings are limited to the Irish artisan food sector and explore identity development through a single SM platform. The applicability and variation of use of the processes across industries would serve to further refine the processes identified.

Practical implications
Practically, the four processes through which identity within a network can be developed using SM can help entrepreneurs to access and position themselves within business networks, gain access to resources and overcome the classic limitations of newness and smallness.

Originality/value
This paper provides a conceptual framework illustrating the processes involved in developing entrepreneurial organisational identity within business networks using SM. This paper adds to a growing literature that places interaction at the heart of identity development and responds to calls to further understanding of the process of identity development for entrepreneurial ventures.