bluuebunny/crossref_metadata_2025_split huggingface dataset:
City identity in existing city future planning or development
Authors: Prommanop Thirak Phim Pha , Wahab Mohammad Hussaini , Amat Rohayah Che 
Published: September 2024

Abstract
As urbanization and modernization continue to shape Malaysia’s cities, balancing progress with preserving city identity is important. Unfortunately, many cities are neglecting their existing identity in urban planning, hindering the image-making and the function of the city. Despite some efforts being made, the focus remains on economic and functional spaces to cater to the growing population. This study seeks to create a framework for Malaysia’s cities that foster a renewed appreciation towards meaningful city characteristics and heritage preservation while encouraging sustainable urban practices. It draws on successful international examples and takes into account Malaysia’s unique historical and cultural background. The absence of specific legislation in Malaysia regarding urban development has pushed the government to draft The Urban Renewal Act, which aims to facilitate redevelopment and revitalization efforts. The government’s ‘MADANI’ policy aims to improve collaboration between policymakers and the public to ensure more humane policies are being implemented.
This paper provides a review of the relationship gap between the city identity and future city planning. The findings of portraying identity strategies in Malaysia’s existing structural plans and its recommendations that could help practitioners, legislators, and decision-makers involved in urban planning matters while ensuring the importance of preserving and enhancing city identity that aligns with Sustainable Development Goal 11 in creating sustainable cities and communities.
The study of the freeze-thaw resistance and carbonation resistance of manufactured sand-RAC based on fly ash and slag powder
Authors: Wei Xiong , Shanjun Zhang , Junjie Yi , Xiaoqing Wang 
Published: September 2024

Abstract
To advance the use of industrial solid waste and recycled concrete, this study explores the impact of fly ash and slag powder on the mechanical properties, freeze–thaw resistance, and carbonation resistance of manufactured sand recycled aggregate concrete (MRAC). Different FSMRAC (Fly Ash and Slag Powder MRAC) mixtures were prepared by varying the amounts of fly ash and slag powder. The results show that fly ash and slag powder enhance the splitting tensile strength of MRAC more than its compressive strength. when the contents of fly ash and slag powder are 0% and 30%, respectively, the FSMRAC attains maximum compressive strength of 48.6 MPa and splitting tensile strength of 3.8 MPa, representing increases of 2.96% and 5.6% in compressive and splitting tensile strengths, respectively, compared to MRAC. A total addition of 30% fly ash and slag powder effectively reduces the loss of mechanical properties under freeze–thaw conditions. When the fly ash-to-slag powder ratio (F:S) exceeds 1.5, it improves carbonation resistance and compressive strength; when the ratio is below 1.5, it enhances splitting tensile strength resistance to freeze–thaw cycles. Slag powder promotes hydration and improves mechanical properties, while fly ash densifies the concrete matrix and lowers the carbonation rate. Response Surface Methodology (RSM) analysis indicates that both materials improve MRAC’s properties. Higher fly ash content benefits compressive strength and carbonation resistance, while higher slag powder content improves splitting tensile strength.
Overcoming challenges: advancements in cutting techniques for high strength-toughness alloys in aero-engines
Authors: Zhao Biao , Wang Yufeng , Peng Jianhao , Wang Xin , Ding Wenfeng , Lei Xiaofei , Wu Bangfu , Zhang Minxiu , Xu Jiuhua , Zhang Liangchi , Das Raj 
Published: September 2024

Abstract
Aero-engines, the core of air travel, rely on advanced high strength-toughness alloys (THSAs) such as titanium alloys, nickel-based superalloys, intermetallics, and ultra-high strength steel. The precision of cutting techniques is crucial for the manufacture of key components, including blades, discs, shafts, and gears. However, machining THSAs pose significant challenges, including high cutting forces and temperatures, which lead to rapid tool wear, reduced efficiency, and compromised surface integrity. This review thoroughly explores the current landscape and future directions of cutting techniques for THSAs in aero-engines. It examines the principles, mechanisms, and benefits of energy-assisted cutting technologies like laser-assisted machining and cryogenic cooling. The review assesses various tool preparation methods, their effects on tool performance, and strategies for precise shape and surface integrity control. It also outlines intelligent monitoring technologies for machining process status, covering aspects such as tool wear, surface roughness, and chatter, contributing to intelligent manufacturing. Additionally, it highlights emerging trends and potential future developments, including multi-energy assisted cutting mechanisms, advanced cutting tools, and collaborative control of structure shape and surface integrity, alongside intelligent monitoring software and hardware. This review serves as a reference for achieving efficient and high-quality manufacturing of THSAs in aero-engines.
A robust approach for FOD detection on runway powered by image deblurring
Authors: Kumari Alka , Dixit Abhishek , Agrawal Pooja 
Published: September 2024

Abstract
Detecting Foreign Object Debris (FOD) on runways is crucial for ensuring flight safety and preventing accidents. However, this task becomes significantly more challenging in adverse weather conditions like rain, snow, and fog. This underscores the need for a robust object detection system capable of functioning effectively in blurred environments. In this study, we propose Deblur model, a dedicated convolutional neural network (CNN) model designed for deblurring tasks. Unique aspect of this study is integration of Deblur model with the You Only Look Once (YOLOv8) object detection architecture. Deblur model aims to enhance FOD detection on runways under blurred conditions. A notable divergence from conventional object detection algorithms that frequently falter in low-visibility situations. Deblur model substantially elevates the quality of input data fed into the YOLOv8 detector. This enhancement in input fidelity directly translates to superior detection accuracy and robustness. This integration is a novel method of addressing the two problems of object detection and deblurring in one framework. We evaluate the effectiveness of this integration through a comparative analysis on a blurred test dataset. The evaluation consists of two scenarios: direct application of the object detection model on the blurred dataset and utilization of the object detection model alongside the Deblur model. Significant improvements in performance metrics of the YOLOv8 object detection model are observed when combined with Deblur model. These enhancements include a 7% increase in recall, 7.7% boost in accuracy, 5.4% rise in mAP50, and a remarkable 11.6% improvement in mAP50-95. Real-time validation confirms the superior performance of our proposed technique compared to the YOLOv8 baseline model. To validate this, a drone equipped with a portable camera captures FOD on the runway, showcasing improved object recognition capabilities across varying levels of image clarity. The broad use of this integrated system goes beyond runway FOD detection. This method may be used to any application that needs accurate detection of objects in low-visibility circumstances, such marine navigation, autonomous driving in bad weather, and surveillance in foggy conditions. Enhancing picture clarity prior to implementing detecting algorithms greatly increase reliability and accuracy.
Design of reliable and fast Schmitt trigger 10T SRAM cells using in-memory computing
Authors: Rani Mucherla Usha , Reddy N Siva Sankara , B Rajendra Naik 
Published: September 2024

Abstract
Microprocessors, integrated data storage systems, and cache memories are just a few applications that can benefit from Static random access memory (SRAM). Computing In memory provides a solution for the von Neumann bottleneck problems. Simultaneously, it removes needless repeated data transmission between CPU and memory. Schmitt trigger was utilized for energy-efficient operation to get high reading and writing capacity. Two cross-coupled inverters with a transistor in between increase the design writing process. Furthermore, voltage boost logic is prioritized to maximize the node capacity. Using two dummy columns and dummy rows in RAM, the Replica technique controls the flow of signals via the core. The simulated results are compared to the designs that already exist. The simulation results show that the leakage power of the proposed design is 0.75 nw at 0.6 volts. The write static noise margin (WSNM) of the proposed cell is twice that of SEDF10T, which can be helpful for high-performance computing applications.
Solidarity and Responsibility
Authors: Sheldrake Philip 
Published: September 2024

AbstractSolidarity is an important public virtue that follows naturally from the concept of community. Solidarity is closely associated with another public virtue, responsibility. Solidarity underlines that our commitment to other people should promote inclusive and equal communities. Solidarity is also related to promoting the “common good.” The “common good” suggests that human relations are not simply utilitarian. They profoundly challenge people with power and/or wealth. The “common good” originates in ancient philosophy but was taken up by theologians such as Augustine and by Catholic Social Teaching. Solidarity also plays a central role in political and liberation theology. The associated virtue of “responsibility” includes “service”—serving our fellow human beings and communities. Responsibility also links to the notion of “civic duty”—that is, engaging with public life in ways that uphold key social values.
Evaluating the impact of an automated drug retrieval cabinet and robotic dispensing system in a large hospital central pharmacy
Authors: Lin Alex C , Gamble Justin M , Gabriel Mina K , Hong Tzu-Yen 
Published: September 2024

Abstract

Purpose
To determine the impact of implementing 2 technologies in succession, the Carousel system and XR2 robot, in a hospital central pharmacy. The study examined the technologies’ impact on workload shifted from fully human-involved, labor-intensive filling from shelves to Carousel and/or XR2, prevention of filling errors, and efficiency.

Methods
Implementation occurred in 3 phases from August 2021 through October 2022. In phase I, medications were manually filled from the shelves for immediate doses and automated dispensing cabinet stock. RobotRx was used for unit-dose (UD) carts. In phase II, the Carousel system was introduced, while RobotRx was used for UD carts. In phase III, the XR2 robot was added and RobotRx was decommissioned. Epic data and time studies were utilized and analyzed with ANOVA.

Results
Over the 3 phases of implementation, workload shifted away from filling from the shelves, with 2,479, 1,044, and 864 orders filled from the shelves for phase I through phase III, respectively. The Carousel workload was 1,234 orders (phase II) and 348 orders (phase III). Nearly 71% of the workload was shifted to the XR2. The overall filling error (prevented) rate did not significantly change from phase I to phase II, remaining at 0.5%. In comparison, the error rate significantly decreased to 0.41% in phase III. Use of the Carousel system resulted in a significant reduction in filling errors compared to manual filling from the shelves. Use of the XR2 robot resulted in a filling error rate of 0%. The savings in time when using both Carousel and XR2 led to a decrease in full-time equivalents of 0.77 for pharmacists and 1.76 for pharmacy technicians.

Conclusion
Carousel and/or XR2 significantly shifted workload from manual filling to automated technologies, decreased filling errors, and improved efficiency, reducing pharmacist and technician workload. Time saved could allow staff to spend more time on patient-centric tasks.
Discussion on “LEAP: the latent exchangeability prior for borrowing information from historical data” by Ethan M. Alt, Xiuya Chang, Xun Jiang, Qing Liu, May Mo, H. Amy Xia, and Joseph G. Ibrahim
Authors: Thomas Shannon D , Kaizer Alexander M 
Published: September 2024

ABSTRACT
This discussion provides commentary on the paper by Ethan M. Alt, Xiuya Chang, Xun Jiang, Qing Liu, May Mo, H. Amy Xia, and Joseph G. Ibrahim entitled “LEAP: the latent exchangeability prior for borrowing information from historical data”. The authors propose a novel method to bridge the incorporation of supplemental information into a study while also identifying potentially exchangeable subgroups to better facilitate information sharing. In this discussion, we highlight the potential relationship with other Bayesian model averaging approaches, such as multisource exchangeability modeling, and provide a brief numeric case study to illustrate how the concepts behind latent exchangeability prior may also improve the performance of existing methods. The results provided by Alt et al. are exciting, and we believe that the method represents a meaningful approach to more efficient information sharing.
Leadership Through Language, Terminology and Representation: Conceptual and Tangible Steps Towards Epistemic Justice Practices
Authors: Devaney Carmel , Mc Gregor Caroline , Buckley Sarah Anne 
Published: September 2024

Abstract
This article is based on research about language, terminology and representation in relation to institutions in Ireland formerly known as ‘Mother and Baby Homes’. Learning from this research informs tangible and conceptual steps towards greater epistemic justice practices for social work. The concept of epistemic justice is used to explore how critical attention to language, terminology and testimony can contribute to promoting rights, countering stigma, recognising diversity and actively challenging misrepresentation, mis-framing and misrecognition. Based on a sample of research findings that demonstrate epistemic injustice, the main themes discussed are identity (motherhood, childhood), places (institutions) and processes (adoption). In the discussion, we draw from participant’s recommendations to outline how social work can provide enhanced leadership in relation to the use of language, terminology and representation and consider this in the context of current research relating to epistemic justice. Given the centrality of language, terminology and representation to social work, there is a significant opportunity within an international context to build on existing knowledge within the profession as well as amongst other professionals, organisations and wider society. To inform this improved ‘knowing and doing’, a number of conceptual and tangible steps to encourage epistemically just practices within social work are identified.
Metabolic network connectivity disturbances in Parkinson's disease: a novel imaging biomarker
Authors: Chen Bei , Chen Xiran , Peng Liling , Liu Shiqi , Tang Yongxiang , Gao Xin 
Published: September 2024

Abstract
The diagnosis of Parkinson’s Disease (PD) presents ongoing challenges. Advances in imaging techniques like 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) have highlighted metabolic alterations in PD, yet the dynamic network interactions within the metabolic connectome remain elusive. To this end, we examined a dataset comprising 49 PD patients and 49 healthy controls. By employing a personalized metabolic connectome approach, we assessed both within- and between-network connectivities using Standard Uptake Value (SUV) and Jensen-Shannon Divergence Similarity Estimation (JSSE). A random forest algorithm was utilized to pinpoint key neuroimaging features differentiating PD from healthy states. Specifically, the results revealed heightened internetwork connectivity in PD, specifically within the somatomotor (SMN) and frontoparietal (FPN) networks, persisting after multiple comparison corrections (P &lt; 0.05, Bonferroni adjusted for 10% and 20% sparsity). This altered connectivity effectively distinguished PD patients from healthy individuals. Notably, this study utilizes 18F-FDG PET imaging to map individual metabolic networks, revealing enhanced connectivity in the SMN and FPN among PD patients. This enhanced connectivity may serve as a promising imaging biomarker, offering a valuable asset for early PD detection.
Methylphenidate reduces spatial attentional bias by modulating fronto-striatal connectivity
Authors: Peled-Avron Leehe , Daood Maryana , Ben-Hayun Rachel , Nevat Michael , Aharon-Peretz Judith , Admon Roee , Tomer Rachel 
Published: September 2024

Abstract
Spatial attention bias reflects tendency to direct attention to specific side in space. This bias reflects asymmetric dopamine (DA) signaling in the striatum. Administration of DA agonists reduces spatial bias, yet the underlying mechanism is not yet clear. To address this, the current study tested whether methylphenidate (MPH; an indirect DA agonist) reduces orienting bias by modulating fronto-striatal connectivity. 54 adults with consistent bias completed the greyscales task which detects subtle biases during fMRI scanning under MPH (20 mg) or placebo, in a double-blind design. As hypothesized, MPH reduced bias by increasing orienting towards non-preferred hemispace, regardless of whether the initial bias was left or right. MPH-induced increases were found in activation of the medial superior frontal gyrus (mSFG: F[1;53] = 4.632, cluster-defining threshold of P &lt; 0.05, minimal cluster size = 0, p_FWE = 0.036, η2 = 0.08) and its functional connectivity with the caudate (left caudate: F[1;53] = 12.664, p_FWE = 0.001, η2 = 0.192; right caudate: F[1;53] = 11.069, p_FWE = 0.002, η2 = 0.172), when orienting towards the non-preferred hemispace. MPH also reduced mSFG activation and fronto-striatal connectivity for the preferred hemispace. Results suggest modulation of frontal excitability due to increased caudate-mSFG functional connectivity. This mechanism may underlie the positive effect of dopaminergic agonists on abnormal patterns of directing attention in space.
Aβ remotely and locally facilitates Alzheimer’s disease tau spreading
Authors: Nabizadeh Fardin ,   Alzheimer’s Disease Neuroimaging Initiative, Nabizadeh Fardin 
Published: September 2024

Abstract
Alzheimer’s disease (AD) is characterized by the accumulation of amyloid-beta plaques initiated approximately 2 decades before the symptom onset followed by build-up and spreading of neurofibrillary tau aggregates. Although it has been suggested that the amyloid-beta amplifies tau spreading the observed spatial disparity called it into question. Yet, it is unclear how neocortical amyloid-beta remotely affects early pathological tau, triggering it to leave the early formation area, and how amyloid-beta facilitates tau aggregate spreading throughout cortical regions. I aimed to investigate how amyloid-beta can facilitate tau spreading through neuronal connections in the Alzheimer’s disease pathological process by combining functional magnetic resonance imaging normative connectomes and longitudinal in vivo molecular imaging data. In total, the imaging data of 317 participants, including 173 amyloid-beta-negative non-demented and 144 amyloid-beta -positive non-demented participants, have entered the study from Alzheimer’s Disease Neuroimaging Initiative. Furthermore, normative resting-state functional magnetic resonance imaging connectomes were used to model tau spreading through functional connections. It was observed that the amyloid-beta in regions with the highest deposition (amyloid-beta epicenter) is remotely associated with connectivity-based spreading of tau pathology. Moreover, amyloid-beta in regions that exhibit the highest tau pathology (tau epicenter) is associated with increased connectivity–based tau spreading to non-epicenter regions. The findings provide a further explanation for a long-standing question of how amyloid-beta can affect tau aggregate spreading through neuronal connections despite spatial incongruity. The results suggest that amyloid-beta pathology can remotely and locally facilitate connectivity-based spreading of tau aggregates.
The neural signature of an erroneous thought
Authors: Steinhauser Klara , Steinhauser Robert , Ernst Benjamin , Maier Martin E , Steinhauser Marco 
Published: September 2024

Abstract
The human brain detects errors in overt behavior fast and efficiently. However, little is known about how errors are monitored that emerge on a mental level. We investigate whether neural correlates of error monitoring can be found during inner speech and whether the involved neural processes differ between these non-motor responses and behavioral motor responses. Therefore, electroencephalographic data were collected while participants performed two versions of a decision task that only differed between these response modalities. Erroneous responses were identified based on participants’ metacognitive judgments. Correlates of error monitoring in event-related potentials were analyzed by applying residue iteration decomposition on stimulus-locked activity. Non-motor responses elicited the same cascade of early error-related negativity and late error positivity as motor responses. An analysis of oscillatory brain activity showed a similar theta response for both error types. A multivariate pattern classifier trained on theta from the motor condition could decode theta from the non-motor condition, demonstrating the similarity of both neural responses. These results show that errors in inner speech are monitored and detected utilizing the same neural processes as behavioral errors, suggesting that goal-directed cognition and behavior are supported by a generic error-monitoring system.
Stable individual differences from dynamic patterns of function: brain network flexibility predicts openness/intellect, intelligence, and psychoticism
Authors: Sassenberg Tyler A , Safron Adam , DeYoung Colin G 
Published: September 2024

Abstract
A growing understanding of the nature of brain function has led to increased interest in interpreting the properties of large-scale brain networks. Methodological advances in network neuroscience provide means to decompose these networks into smaller functional communities and measure how they reconfigure over time as an index of their dynamic and flexible properties. Recent evidence has identified associations between flexibility and a variety of traits pertaining to complex cognition including creativity and working memory. The present study used measures of dynamic resting-state functional connectivity in data from the Human Connectome Project (n = 994) to test associations with Openness/Intellect, general intelligence, and psychoticism, three traits that involve flexible cognition. Using a machine-learning cross-validation approach, we identified reliable associations of intelligence with cohesive flexibility of parcels in large communities across the cortex, of psychoticism with disjoint flexibility, and of Openness/Intellect with overall flexibility among parcels in smaller communities. These findings are reasonably consistent with previous theories of the neural correlates of these traits and help to expand on previous associations of behavior with dynamic functional connectivity, in the context of broad personality dimensions.