Miracle-dz/UniFAR-FTUs huggingface dataset:
DIFFERENTIAL FORMS IN MANIFOLDS WITH BOUNDARY

The theory of harmonic forms in Riemannian manifolds may be regarded as a generalization of potential theory. It is therefore natural that the boundary value problems of this theory which generalize the classical Dirichlet and Neumann problems should play an important role in the theory. Such theorems were conjectured by Tucker (4a). The present paper is concerned with some theorems regarding closed forms, which are necessary for the proof of the boundary value existence theorems for harmonic fields in a Riemannian manifold with boundary. In an accompanying paper, by D. C. Spencer and the author, the results of this paper will be used in the proofs of these theorems. We consider closed forms in a finite regular manifold with boundary, and prove results which generalize two theorems of G. de Rham (3) for a closed manifold. To extend the technique of de Rham, we make use of the relative, or modular, homology theory introduced by Lefschetz (2). The main results of the paper are contained in Theorems 2 and 6. Theorems 1, 3, and 5 are analogues of de Rham's first theorem, and Theorems 2, 4 and 6 of his second theorem. Theorems 3 to 6 inclusive were conjectured in substantially their present form by Tucker (4b).
An Automatic Control Perspective on Parameterizing Generative Adversarial Network

This article presents a new perspective from control theory to interpret and solve the instability and mode collapse problems of generative adversarial networks (GANs). The dynamics of GANs are parameterized in the function space and control directed methods are applied to investigate GANs. First, the linear control theory is utilized to analyze and understand GANs. It is proved that the stability depends only on control parameters. Second, a proportional–integral–derivative (PID) controller is designed to improve its stability. GANs can be controlled to adaptively generate images by an overshoot rate that is only related to the PID control parameters. Third, a new PIDGAN is derived with a theoretical guarantee of stability. Fourth, to exploit the nonlinear characteristics of GANs, the nonlinear control theory is applied to further analyze GANs and develop a feedback linearization control-based PIDGAN named NPIDGAN. Both PIDGAN and NPIDGAN not only improve stability but also prevent mode collapse. With five datasets covering a wide variety of image domains, the proposed models achieve superior performance with $1024\times 1024$ resolution compared with the state-of-the-art GANs, even when data are limited.
A Traveling Waves Perspective on Temporal Binding

Abstract Brain oscillations are involved in many cognitive processes, and several studies have investigated their role in cognition. In particular, the phase of certain oscillations has been related to temporal binding and integration processes, with some authors arguing that perception could be an inherently rhythmic process. However, previous research on oscillations mostly overlooked their spatial component: how oscillations propagate through the brain as traveling waves, with systematic phase delays between brain regions. Here, we argue that interpreting oscillations as traveling waves is a useful paradigm shift to understand their role in temporal binding and address controversial results. After a brief definition of traveling waves, we propose an original view on temporal integration that considers this new perspective. We first focus on cortical dynamics, then speculate about the role of thalamic nuclei in modulating the waves, and on the possible consequences for rhythmic temporal binding. In conclusion, we highlight the importance of considering oscillations as traveling waves when investigating their role in cognitive functions.
Pupillary response is associated with the reset and switching of functional brain networks during salience processing

The interface between processing internal goals and salient events in the environment involves various top-down processes. Previous studies have identified multiple brain areas for salience processing, including the salience network (SN), dorsal attention network, and the locus coeruleus-norepinephrine (LC-NE) system. However, interactions among these systems in salience processing remain unclear. Here, we simultaneously recorded pupillometry, EEG, and fMRI during an auditory oddball paradigm. The analyses of EEG and fMRI data uncovered spatiotemporally organized target-associated neural correlates. By modeling the target-modulated effective connectivity, we found that the target-evoked pupillary response is associated with the network directional couplings from late to early subsystems in the trial, as well as the network switching initiated by the SN. These findings indicate that the SN might cooperate with the pupil-indexed LC-NE system in the reset and switching of cortical networks, and shed light on their implications in various cognitive processes and neurological diseases.
Deployment of machine learning algorithms to predict sepsis: systematic review and application of the SALIENT clinical AI implementation framework

Abstract Objective To retrieve and appraise studies of deployed artificial intelligence (AI)-based sepsis prediction algorithms using systematic methods, identify implementation barriers, enablers, and key decisions and then map these to a novel end-to-end clinical AI implementation framework. Materials and Methods Systematically review studies of clinically applied AI-based sepsis prediction algorithms in regard to methodological quality, deployment and evaluation methods, and outcomes. Identify contextual factors that influence implementation and map these factors to the SALIENT implementation framework. Results The review identified 30 articles of algorithms applied in adult hospital settings, with 5 studies reporting significantly decreased mortality post-implementation. Eight groups of algorithms were identified, each sharing a common algorithm. We identified 14 barriers, 26 enablers, and 22 decision points which were able to be mapped to the 5 stages of the SALIENT implementation framework. Discussion Empirical studies of deployed sepsis prediction algorithms demonstrate their potential for improving care and reducing mortality but reveal persisting gaps in existing implementation guidance. In the examined publications, key decision points reflecting real-word implementation experience could be mapped to the SALIENT framework and, as these decision points appear to be AI-task agnostic, this framework may also be applicable to non-sepsis algorithms. The mapping clarified where and when barriers, enablers, and key decisions arise within the end-to-end AI implementation process. Conclusions A systematic review of real-world implementation studies of sepsis prediction algorithms was used to validate an end-to-end staged implementation framework that has the ability to account for key factors that warrant attention in ensuring successful deployment, and which extends on previous AI implementation frameworks.
The Hidden Costs and Benefits of Monitoring in the Gig Economy

Monitoring is ubiquitous in the gig economy wherein the workforce is geographically dispersed. However, workers are often reluctant to be monitored because of privacy concerns, resulting in a hidden economic cost for employers as workers demand higher wages for monitored jobs. We investigate how three common dimensions of monitoring affect workers’ willingness to accept monitored jobs through online experiments on two gig economy platforms. The three dimensions of monitoring are intensity (how much information is collected), transparency (whether the monitoring policy is disclosed to workers), and control (whether workers can remove sensitive information). We find that, as the monitoring intensity increases, workers become less willing to accept monitoring because of elevated privacy concerns. Furthermore, being transparent about the monitoring policy increases workers’ willingness to accept monitoring only when the monitoring intensity is low. Interestingly, providing control over high-intensity monitoring does not significantly reduce workers’ privacy concerns, rendering this well-intentioned policy ineffective. Finally, females are more willing to accept monitored jobs than males as they perceive higher payment protection from monitoring and have lower privacy concerns. On average, the hourly wage compensation required for gig workers to accept monitoring is 1.6∼1.8 dollars, which amounts to roughly 28.6%∼37.5% of their average hourly wage.
Factors Impacting the Behavioral Intention to Use Social Media for Knowledge Sharing: Insights from Disaster Relief Practitioners

Aim/Purpose: The primary purpose of this study is to investigate the factors that impact the behavioral intention to use social media (SM) for knowledge sharing (KS) in the disaster relief (DR) context. Background: With the continuing growth of SM for KS in the DR environment, disaster relief organizations across the globe have started to realize its importance in streamlining their processes in the post-implementation phase. However, SM-based KS depends on the willingness of members to share their knowledge with others, which is affected by several technological, social, and organizational factors. Methodology: A survey was conducted in Somalia to gather primary data from DR practitioners, using purposive sampling as the technique. The survey collected 214 valid responses, which were then analyzed with the PLS-SEM approach. Contribution: The study contributes to an understanding of the real-life hurdles faced by disaster relief organizations by expanding on the C-TAM-TPB model with the inclusion of top management support, organizational rewards, enjoyment in helping others, knowledge self-efficacy, and interpersonal trust factors. Additionally, it provides useful recommendations to managers of disaster relief organizations on the key factors to consider. Findings: The findings recorded that perceived usefulness, ease of use, top management support, enjoyment in helping others, knowledge self-efficacy, and interpersonal trust were critical factors in determining behavioral intention (BI) to use SM-based KS in the DR context. Furthermore, the mediator variables were attitude, subjective norms, and perceived behavioral control. Recommendations for Practitioners: Based on the research findings, it was determined that management should create different discussion forums among the disaster relief teams to ensure the long-term use of SM-based KS within DR organizations. They should also become involved in the discussions for disaster-related knowledge such as food supplies, shelter, or medical relief that disaster victims need. Disaster relief managers should consider effective and adequate training to enhance individual knowledge and self-efficacy since a lack of training may increase barriers and difficulties in using SM for KS during a DR process. Recommendation for Researchers: The conceptual model, further empirically investigated, can be employed by other developing countries in fostering acceptance of SM for KS during disaster relief operations. Impact on Society: Disaster relief operations can be facilitated using social media by considering the challenges DR practitioners face during emergencies. Future Research: In generalizing this study’s findings, other national or global disaster relief organizations should consider, when applying and testing, the research instruments and proposed model. The researchers may extend this study by collecting data from managers or administrators since they are different types of users of the SM-based KS system.
Discoidin domain receptors; an ancient family of collagen receptors has major roles in bone development, regeneration and metabolism

The extracellular matrix (ECM) niche plays a critical role in determining cellular behavior during bone development including the differentiation and lineage allocation of skeletal progenitor cells to chondrocytes, osteoblasts, or marrow adipocytes. As the major ECM component in mineralized tissues, collagen has instructive as well as structural roles during bone development and is required for bone cell differentiation. Cells sense their extracellular environment using specific cell surface receptors. For many years, specific β1 integrins were considered the main collagen receptors in bone, but, more recently, the important role of a second, more primordial collagen receptor family, the discoidin domain receptors, has become apparent. This review will specifically focus on the roles of discoidin domain receptors in mineralized tissue development as well as related functions in abnormal bone formation, regeneration and metabolism.
Matrices and Division by Zero z/0 = 0

In this paper, a new viewpoint of the division by zero z/0 = 0 in matrices is introduced and the results will show that the division by zero is our elementary and fundamental mathematics. New and practical meanings for many mathematical and physical formulas for the denominator zero cases may be given. Furthermore, a new space idea for the point at infinity for the Eucleadian plane is also introduced.
Novel Adaptive Region Spectral–Spatial Features for Land Cover Classification With High Spatial Resolution Remotely Sensed Imagery

Spectral–spatial features are important for ground target identification and classification with high spatial resolution remotely sensed (HSRRS) Imagery. In this article, two novel features, named the Gaussian-weighting spectral (GWS) feature and the area shape index (ASI) feature, are proposed to complement the deficiency of the basic image feature for land cover classification with HSRRS imagery. The proposed GWS feature is an adaptive region-based feature that aims to improve the spectral homogeneity of a local area surrounding a pixel. Additionally, it is well known that the spectral feature is inadequate for classifying HSRRS imagery. Therefore, one spatial feature called the ASI feature is proposed here to describe the relationship between the area and shape for an adaptive region around each pixel. The proposed GWS and ASI features coupled with the basic red–green–blue (RGB) feature are fed into a supervised classifier to obtain the final classification map. Experiments based on four real HSRRS images demonstrate that the proposed GWS and ASI features are capable of improving classification accuracies compared with some cognate state-of-the-art methods. Moreover, the experiments also reveal that the proposed spectral–spatial features can complement each other for enhancing the classification performance with HSRRS images.
The Patterns of Restriction Fragment of Several Enzymes to Distinguish Toxoplasma gondii Isolates Virulent and Avirulent Strains using GRA1 and GRA7 Genetic Marker

Toxoplasma gondii pathogenicity depends on the type derived from a clonal population. A genetic analysis of the locus has been carried out to determine the different genotypes of T. gondii (strain types I, II, and III) that are associated with human toxoplasmosis. The several genotypes of T. gondii (strain types I, II, and III) that are linked to human toxoplasmosis have been identified through genetic study of the locus. In this investigation, PCR-RFLP was found to be a useful, and simple method genotypic characterization. The objective of this study was to genotyping characterize T. gondii RH and BEV strains isolates by PCR-RFLP using several restriction enzymes. T. gondii tachyzoite DNA was extracted and amplified by PCR using dense granule genetic markers (GRA1 and GRA7) designed with Primer3plus. The amplification were digested using the restriction enzymes. The PCR-RFLP amplified dense granule products was used to classify strains into two genotypes of T. gondii (virulent and avirulent). The results demonstrated that the RFLP patterns of the GRA1 and GRA7 gene area digested by DdeI, MvaI, HinfI, RsaI, and Sau96I enzymes can be used to identify virulent or avirulent strains of T. gondii. Toxoplasma gondii RH and BEV strain produced different digestion product which can be used to distinguished the strains.
Summer growth rates and annual yields of perennial ryegrass (Lolium perenne L.) in the Upper North Island are expected to decline as a result of climate change

Evaluating the ability of perennial ryegrass to continue underpinning New Zealand’s low-cost dairy production systems under future climate change scenarios requires a modelling approach. In this study, climate projections for different climate change scenarios were used in the BASGRA pasture model to predict changes in annual yields and seasonal pasture growth rate patterns of perennial ryegrass. These predictions, including uncertainty, were made for the years 2010-2014, 2040-2044 and 2090-2094 in 14 dairy-dominant subregions in the Upper North Island of New Zealand. The suitability of perennial ryegrass is expected to decline in the future across all subregions, with worse outcomes expected under higher atmospheric greenhouse gas levels. Winter is expected to be the season least affected by climate change and summer the most affected. Late-winter/spring is predicted to become the main growing season, followed by late-autumn/early-winter. The ability offarmers to adapt their farming practices is essential in remaining profitable and internationally competitive.
Influence of social bots in information warfare: A case study on @UAWeapons Twitter account in the context of Russia–Ukraine conflict

During the Russia–Ukraine conflict, social media has become an outlet for public opinion; therefore, besides the hot war, information warfare is also taking place. It was discovered that a large number of new social bot accounts had emerged on Twitter since the outbreak of the conflict. In particular, the Twitter account @UAWeapons has grown its following by hundreds of thousands in fewer than 30 days and has established itself as an influential opinion leader. Through data mining and three different analysis methods, this study investigated how social bots grew to influence public opinion. Specifically, time-series analysis revealed an unusual pattern of “pulsing” changes in the number of tweets posted by @UAWeapons over time. The content analysis illustrated that the account posted biased tweets in favor of Ukraine under the guise of being a neutral messenger, which led to frequent retweets from social bots with similar opinions. Finally, the results of the social network analysis indicated that @UAWeapons’ rapid growth might be attributed to a strategy of network clustering implemented by a core group of social bot accounts.
Smartphone-based prenatal attachment education application design improving maternal and fetal attachment to high-risk pregnant mothers at Putri Ayu Health Center Jambi City

Background: The prevalence of high-risk pregnancies in the world is still relatively high. Approximately 10-30% of mothers who undergo routine antenatal care are diagnosed with high-risk pregnancies and of these, 70-80% experience perinatal mortality and morbidity. The psychological impact of high-risk pregnancy is anxiety, stress, and the mother experiencing a crisis that can affect the relationship between the mother and the fetus. This condition can also continue in the relationship between mother and baby after birth. Therefore, it is necessary to make efforts to increase the attachment of mother and fetus, one of which can be done by providing education. The purpose of this study was to determine the effect of Android-based Prenatal Attachment Education Applications on Maternal and Fetal Attachment in High-Risk Pregnant Women. Methods: This type of research is quantitative with a quasi-experimental design study that uses a one group pretest - posttest design without control group. The intervention provided was in the form of prenatal attachment education packaged in an application via mobile phones. The research sample was 40 pregnant women at Putri Ayu Public Health Center, Jambi City. The inclusion criteria in this study were pregnant women who could read and write. Exclusion criteria were respondents who were not willing to participate in the study. Results: Based on the results of the above analysis, it can be seen that Sig is 0.000 < 0.001, which means that H0 is rejected and Ha is accepted. In other words, there is a significant relationship between the application of prenatal attachment education with maternal and fetal attachment. Conclusion: maternal and fetal attachment can be improved with prenatal attachment education applications, for that it is expected that the puskesmas implement prenatal attachment education applications using mobile phones so that they can increase maternal and fetal attachment.
Effects of Sea-Ice Persistence on the Diet of Adélie Penguin (Pygoscelis adeliae) Chicks and the Trophic Differences between Chicks and Adults in the Ross Sea, Antarctica

Simple Summary The Adélie penguin, Pygoscelis adeliae, is one of the most abundant predators in the Antarctic. Its survival depends on numerous factors, including the presence of prey, closely related to sea ice. By changing sea-ice dynamics, climate change could affect its diet and recruitment. The aim of this study is to investigate, by means of stable isotope analysis of their faeces, penguin chicks’ diets in four colonies characterised by differing sea-ice persistence. In order to investigate any differences in diet between chicks and adults, the faeces of the latter were also collected and analysed. The study found that the contribution of krill to the chicks’ diets is generally greater than that of fish but that the proportion depends on the spatiotemporal variability of sea-ice dynamics. In addition, where sea ice was more persistent, the contribution of fish was lower in chicks than in adults. The less negative δ13C values of adults than chicks suggest that adults catch prey inshore for themselves and offshore for chicks. The expected variations in sea-ice dynamics and thus prey availability due to climate change might therefore modify the penguins’ diet and thus the role of this dominant endemic species in the Antarctic food web. Abstract In Antarctica, prey availability for the mesopredator Adélie penguin, Pygoscelis adeliae, depends on sea-ice dynamics. By affecting cycles of sea-ice formation and melt, climate change could thus affect penguin diet and recruitment. In the light of climate change, this raises concerns about the fate of this dominant endemic species, which plays a key role in the Antarctic food web. However, few quantitative studies measuring the effects of sea-ice persistence on the diet of penguin chicks have yet been conducted. The purpose of this study was to fill this gap by comparing penguin diets across four penguin colonies in the Ross Sea and evaluating latitudinal and interannual variation linked to different sea-ice persistence. Diet was evaluated by analysing the δ13C and δ15N values of penguin guano, and sea-ice persistence by means of satellite images. Isotopic values indicate that penguins consumed more krill in colonies with longer sea-ice persistence. In these colonies, the δ13C values of chicks were lower and closer to the pelagic chain than those of adults, suggesting that the latter apparently catch prey inshore for self-feeding and offshore for their chicks. The results indicate that sea-ice persistence is among the principal factors that influence the spatiotemporal variability of the penguins’ diet.