Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular Mechanisms of Injury in HIV-Associated Nephropathy

HIV-associated nephropathy (HIVAN) is an important cause of secondary focal glomerulosclerosis that occurs primarily in persons of African ancestry with advanced HIV disease. Although HIVAN is characterized by severe proteinuria and rapid progression to end stage renal disease without treatment, the phenotype is markedly attenuated by treatment with antiretroviral medications. HIV infection of glomerular and tubular epithelial cells and subsequent viral gene expression is a key contributor to HIVAN pathogenesis and the kidney can serve as reservoir for HIV strains that differ those in blood. HIV gene expression in renal epithelial cells leads to dysregulation of cellular pathways including cell cycle, inflammation, cell death, and cytoskeletal homeostasis. Polymorphisms in the APOL1 gene explain the marked predilection of HIVAN to occur in persons of African descent and HIVAN. Since HIVAN has the strongest association with APOL1 genotype of any of the APOL1-associated nephropathies, studies to determine the mechanisms by which HIV and APOL1 risk variants together promote kidney injury hold great promise to improve our understanding of the pathogenesis of APOL1-mediated kidney diseases.
Multi-chart generative surface modeling

This paper introduces a 3D shape generative model based on deep neural networks. A new image-like (i.e., tensor) data representation for genus-zero 3D shapes is devised. It is based on the observation that complicated shapes can be well represented by multiple parameterizations (charts), each focusing on a different part of the shape. The new tensor data representation is used as input to Generative Adversarial Networks for the task of 3D shape generation. The 3D shape tensor representation is based on a multi-chart structure that enjoys a shape covering property and scale-translation rigidity. Scale-translation rigidity facilitates high quality 3D shape learning and guarantees unique reconstruction. The multi-chart structure uses as input a dataset of 3D shapes (with arbitrary connectivity) and a sparse correspondence between them. The output of our algorithm is a generative model that learns the shape distribution and is able to generate novel shapes, interpolate shapes, and explore the generated shape space. The effectiveness of the method is demonstrated for the task of anatomic shape generation including human body and bone (teeth) shape generation.
Emotional Labor in the Sharing Economy

The peer-to-peer nature of the sharing economy encourages participants to alter their behavior in ways that resemble traditional notions of emotional labor. A key element in this shift lies in the coercive nature of feedback mechanisms which condition both providers and consumers to perform emotional labor during service encounters. Using survey data from 207 sharing economy consumers in the US, we show how different facets of the feedback mechanisms employed by sharing economy services influence consumers’ emotional labor. In addition, we show how platforms and their policies matter in encouraging emotional labor, indicating the need to analyze the topic on a fine-grained level. We conclude by deriving propositions for future research and practical recommendations
Findings From a Prospective Randomized Controlled Trial of an Individualized Music Listening Program for Persons With Dementia

Music & Memory (M&M) is a passive music intervention that uses personalized music playlists delivered on digital music players. This program has been increasingly adopted in nursing homes across the United States to facilitate communication, engagement, and socialization among persons with dementia (PWDs); however, few studies have evaluated the program’s effect on PWDs’ outcomes. In the present study, a randomized controlled crossover design was used to examine the impact of the M&M program on 59 PWDs in 10 nursing homes over a 14-week period. Residents’ evaluated outcomes included agitation, behavioral symptoms, and use of psychotropic medications. Although trends supported the positive effects of M&M, no statistically significant differences were found in any of the outcomes measured over time. Methodological limitations withstanding, these findings call into question the effectiveness of the M&M program and the ability of facility staff to implement this intervention with fidelity.
Single-molecule FRET reveals proofreading complexes in the large fragment of Bacillus stearothermophilus DNA polymerase I

There is increasing interest in the use of DNA polymerases (DNA pols) in next-generation sequencing strategies. These methodologies typically rely on members of the A and B family of DNA polymerases that are classified as high-fidelity DNA polymerases. These enzymes possess the ability to selectively incorporate the correct nucleotide opposite a templating base with an error frequency of only 1 in 106 insertion events. How they achieve this remarkable fidelity has been the subject of numerous investigations, yet the mechanism by which these enzymes achieve this level of accuracy remains elusive. Several smFRET assays were designed to monitor the conformational changes associated with the nucleotide selection mechanism(s) employed by DNA pols. smFRET has also been used to monitor the movement of DNA pols along a DNA substrate as well as to observe the formation of proof-reading complexes. One member among this class of enzymes, the large fragment of Bacillus stearothermophilus DNA polymerase I (Bst pol I LF), contains both 5′→3′ polymerase and 3′→5′ exonuclease domains, but reportedly lacks exonuclease activity. We have designed a smFRET assay showing that Bst pol I LF forms proofreading complexes. The formation of proofreading complexes at the single molecule level is strongly influenced by the presence of the 3′ hydroxyl at the primer-terminus of the DNA substrate. Our assays also identify an additional state, observed in the presence of a mismatched primer-template terminus, that may be involved in the transfer of the primer-terminus from the polymerase to the exonuclease active site.
Membrane-associated human tyrosinase is an enzymatically active monomeric glycoprotein

Human tyrosinase (hTyr) is a Type 1 membrane bound glycoenzyme that catalyzes the initial and rate-limiting steps of melanin production in the melanosome. Mutations in the Tyr gene are linked to oculocutaneous albinism type 1 (OCA1), an autosomal recessive disorder. Currently, the application of enzyme replacement therapy for a treatment of OCA1 is hampered by the absence of pure hTyr. Here, full-length hTyr (residues 1–529) was overexpressed in Trichoplusia ni larvae infected with a baculovirus, solubilized with detergent and purified using chromatography. Michaelis-Menten kinetics, enzymatic specific activity, and analytical ultracentrifugation were used to compare the hTyr in detergent with the soluble recombinant intra-melanosomal domain, hTyrCtr (residues 19–469). Active hTyr is monomeric in detergent micelles suggesting no stable interactions between protein molecules. Both, hTyr and hTyrCtr, exhibited similar enzymatic activity and ligand affinity in L-DOPA and L-Tyrosine reactions. In addition, expression in larvae is a scalable process that will allow high yield protein production. Thus, larval production of enzymatically active human tyrosinase potentially could be a useful tool in developing a cure for OCA1.
On the recognition of the alphabet of the sign language through size functions

Size functions are integer-valued functions which represent both qualitative and quantitative properties of visual shape. In this paper the use of size functions for the understanding of the alphabet of sign language is described. First, a family of size functions able to capture important aspects of shape from the apparent outline of the various signs are presented and motivated. Each sign is represented by means of a feature vector computed from the proposed family of size functions. Then, a training set of feature vectors is built from real images. Finally, the k-nearest-neighbor rule is employed for the classification of feature vectors computed from previously unseen signs. The reported experiments indicate that size functions can be extremely effective for the recognition of signs even in the presence of shape changes due to difference in hands, pose, style of signing, and viewpoint.
Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices

Given a large matrix A ∈ Rn×d, we consider the problem of computing a sketch matrix B ∈ R`×d which is significantly smaller than but still well approximates A. We are interested in minimizing the covariance error ‖AA−BB‖2. We consider the problems in the streaming model, where the algorithm can only make one pass over the input with limited working space. The popular Frequent Directions algorithm of (Liberty, 2013) and its variants achieve optimal space-error tradeoff. However, whether the running time can be improved remains an unanswered question. In this paper, we almost settle the time complexity of this problem. In particular, we provide new space-optimal algorithms with faster running times. Moreover, we also show that the running times of our algorithms are near-optimal unless the state-of-the-art running time of matrix multiplication can be improved significantly.
Towards a Model of Collaborative Intention: An Empirical Investigation of a Massive Online Open Course (MOOC)

Disentangling factors that affect one’s intention to collaborate is an important endeavor for management education, especially for globally dispersed groups of students. Drawing on a synthesis of four theories, we advance a model of collaboration intentions that embodies both individual and communal level drivers of individuals’ intention to participate in virtual collaboration. The model is validated based on data collected from 2,517 participants in a Massive Online Open Course (MOOC). Results demonstrate that attitudes towards virtual collaboration are predicted by both collaborative outcome expectancy and communal support expectancy. Additionally, we reveal that collaborative outcome expectancy is predicated on individuals’ belief about his/her ability to collaborate whereas communal support expectancy is impacted by the individual’s perception of communal influence.
Causal Bandits with Propagating Inference

Bandit is a framework for designing sequential experiments. In each experiment, a learner selects an arm $A \in \mathcal{A}$ and obtains an observation corresponding to $A$. Theoretically, the tight regret lower-bound for the general bandit is polynomial with respect to the number of arms $|\mathcal{A}|$. This makes bandit incapable of handling an exponentially large number of arms, hence the bandit problem with side-information is often considered to overcome this lower bound. Recently, a bandit framework over a causal graph was introduced, where the structure of the causal graph is available as side-information. A causal graph is a fundamental model that is frequently used with a variety of real problems. In this setting, the arms are identified with interventions on a given causal graph, and the effect of an intervention propagates throughout all over the causal graph. The task is to find the best intervention that maximizes the expected value on a target node. Existing algorithms for causal bandit overcame the $\Omega(\sqrt{|\mathcal{A}|/T})$ simple-regret lower-bound; however, their algorithms work only when the interventions $\mathcal{A}$ are localized around a single node (i.e., an intervention propagates only to its neighbors). We propose a novel causal bandit algorithm for an arbitrary set of interventions, which can propagate throughout the causal graph. We also show that it achieves $O(\sqrt{ \gamma^*\log(|\mathcal{A}|T) / T})$ regret bound, where $\gamma^*$ is determined by using a causal graph structure. In particular, if the in-degree of the causal graph is bounded, then $\gamma^* = O(N^2)$, where $N$ is the number $N$ of nodes.
Designing Data Governance in Platform Ecosystems

As platform ecosystems such as Facebook or Twitter are rapidly growing through platform users’ data contribution, the importance of data governance has been highlighted. Platform ecosystems, however, face increasing complexity derived from the business context such as multiple parties’ participation. How to share control and decision rights about data assets with platform users is regarded as a significant governance design issue. However, there is a lack of studies on this issue. Existing design models focus on the characteristics of enterprises. Therefore, there is limited support for platform ecosystems where there are different types of context and complicated relationships. To deal with the issue, this paper proposes a novel design approach for data governance in platform ecosystems including design principles, contingency factors and an architecture model. Case studies are performed to illustrate the practical implications of our suggestion.
Determinants of participation and risk factor control according to attendance in cardiac rehabilitation programmes in coronary patients in Europe: EUROASPIRE IV survey

Aim The purpose of this study was to describe the proportions of patients referred to and attending cardiac rehabilitation programmes in Europe and to compare lifestyle and risk factor targets achieved according to participation in a cardiac rehabilitation programme. Methods The EUROASPIRE IV cross-sectional survey was undertaken in 78 centres from 24 European countries. Consecutive patients aged <80 years with acute coronary syndromes and/or revascularization procedures were interviewed at least six months after their event. Results A total of 7998 patients (24% females) were interviewed. Overall, 51% were advised to participate in a cardiac rehabilitation programme and 81% of them attended at least half of the sessions; being 41% of the study population. Older patients, women, those at low socio-economic status or enrolled with percutaneous coronary intervention and unstable angina, as well as those with a previous history of coronary disease, heart failure, hypertension or dysglycaemia were less likely to be advised to follow a cardiac rehabilitation programme. People smoking prior to the recruiting event were less likely to participate. The proportions of patients achieving lifestyle targets were higher in the cardiac rehabilitation programme group as compared to the non-cardiac rehabilitation programme group: stopping smoking (57% vs 47%, p < 0.0001), recommended physical activity levels (47% vs 38%, p < 0.0001) and body mass index<30 kg/m2 (65% vs 61%, p=0.0007). However, there were no differences in the blood pressure, lipids and glucose control. Patients who attended a cardiac rehabilitation programme had significantly lower anxiety and depression scores and better medication adherence. Conclusions Only half of all coronary patients were referred and a minority attended a cardiac rehabilitation programme. Those attending were more likely to achieve lifestyle targets, had lower depression and anxiety, and better medication adherence. There is still considerable potential to further reduce cardiovascular risk by increasing uptake and fully integrating secondary prevention and cardiac rehabilitation to provide a modern preventive cardiology programme.
How Do IT-related Traits Drive the Internet Use of Mature Adults? The Interplay of Curiosity and Control

It can frequently be observed that mature adults use the Internet differently as younger members of society. We propose a model based on IT-related traits to conceptualize the Internet use behavior of mature adults, specifically focusing on curiosity- and control-related traits. We empirically tested our model by investigating the duration and intensity of mature adults’ Internet use. The results reveal that traits reflecting ‘curiosity’ (Personal Innovativeness in IT and Computer Playfulness) explain variations in the duration of Internet use, while traits reflecting ‘control’ (Computer Self-Efficacy and Computer Anxiety) predict the intensity to which mature adults make use of the Internet. Our paper thereby contributes to research on post-acceptance variations and on individual differences in IT use.
Antecedents and Consequences of Time Pressure in Scrum Projects: Insights from a Qualitative Study

Time pressure represents one of the most critical factors associated with software development project failure. However, its role in previous research is limited to traditional development approaches and is also inconclusive, suggesting both negative and positive effects, while others argue for dependence on the level of time pressure. In the context of agile software development projects, particularly Scrum, we seek to analyze the role of time pressure in software development projects and aim to develop a better understanding of its antecedents and consequences. We apply an exploratory, interview-based research approach grounded in data and complemented by thematic analysis. Our findings support a differentiated picture of time pressure, revealing that not all antecedents equally lead to negative consequences and that effects are dependent not only on intensity but also on temporality of time pressure. Understanding antecedents and consequences serves organizations to advantageously manage time pressure.
On the Economies of Scale and Budget Allocations in Information Technology Services Provision

This study reexamines some fundamental questions in the network era of computing using the data after 1995 when firms have made significant investments in newer types of IT systems. Our findings suggest that firms realize some economies of scale in IT services as they grow in size. We also find that the personnel-hardware ratio is not independent of IT budget. Finally, we find that personnelhardware ratio was declining during 1999-2003 period in response to changes in factor prices of hardware and personnel. We discuss implications of these results for academic research and for managerial practice.
Remineralizing Effectiveness of Calcium Sucrose Phosphate and Fluoride Dentifrices: An In vitro Study

Context: Dentifrices-containing remineralizing agents are known to be effective in remineralization of early enamel lesions. Aims: This study aimed to compare and evaluate the changes in surface roughness, surface morphology, and mineral content of demineralized enamel lesion after treatment with dentifrices-containing sodium monofluorophosphate, amine fluoride, and Anticay® (calcium sucrose phosphate with inorganic amorphous calcium phosphate). Settings and Design: This was an in vitro study. Subjects and Methods: Eighteen extracted maxillary molars were decoronated and sectioned into four to obtain 72 specimens. Specimens were demineralized and randomly divided into four different test groups: Group A: no treatment (control), Group B: sodium monofluorophosphate dentifrice (Colgate), Group C: amine fluoride dentifrice (Amflor), Group D: Anticay® dentifrice (EnaFix) and subjected to pH-cycling for 4 weeks. After 4 weeks, they were assessed using a profi lometer and scanning electron microscope (SEM)-energy dispersive X-ray analysis (EDAX) for changes in surface roughness, surface morphology, and mineral content. Statistical Analysis Used: Intergroup comparison was done using repeated measures ANOVA. Results: Intergroup comparison revealed no significant difference in surface roughness and mineral content after remineralization between the groups. SEM images showed mineral deposition in all the dentifrice groups obliterating the defects caused due to demineralization. Conclusions: Sodium monofluorophosphate, amine fluoride-containing dentifrices, and calcium sucrose phosphate with inorganic amorphous calcium phosphate-containing dentifrice were found equivocal in their remineralizing effectiveness of early enamel lesions.
Delay-tolerant networking: an approach to interplanetary Internet

Increasingly, network applications must communicate with counterparts across disparate networking environments characterized by significantly different sets of physical and operational constraints; wide variations in transmission latency are particularly troublesome. The proposed Interplanetary Internet, which must encompass both terrestrial and interplanetary links, is an extreme case. An architecture based on a "least common denominator" protocol that can operate successfully and (where required) reliably in multiple disparate environments would simplify the development and deployment of such applications. The Internet protocols are ill suited for this purpose. We identify three fundamental principles that would underlie a delay-tolerant networking (DTN) architecture and describe the main structural elements of that architecture, centered on a new end-to-end overlay network protocol called Bundling. We also examine Internet infrastructure adaptations that might yield comparable performance but conclude that the simplicity of the DTN architecture promises easier deployment and extension.
Broadband access in Korea: experience and future perspective

With the growing popularity of the Internet, Korea has been successful in providing broadband Internet services to the level of universal service. More than 70 percent of households have high-speed Internet connection, and their lives have been changed dramatically. The cutting edge technology of broadband Internet has a profound impact on many aspects of the economy, education, entertainment, and social culture. This article addresses the experiences and future perspectives of KT (formerly Korea Telecom) in providing the broadband network and services in Korea. We present our experiences in the deployment of the world's largest ADSL network, and our ongoing deployment of VDSL and WLAN. Based on the accomplishment in broadband access, we also provide a forecast on the next generation of broadband services and the corresponding technologies required to support these services.
Enabling the Mapping of Internet of Things Ecosystem Business Models Through Roles and Activities in Value Co-creation

The increasing connectivity provided by the Internet of Things (IoT) supports novel business opportunities for actors’ overlapping service systems. Therefore, the co-creative nature of IoT business needs to be further studied. This paper contributes to the understudied area of IoT ecosystem dynamics by reporting an empirical study on a European IoT initiative and describing different actor roles and activities in the IoT use cases, and their implications for IoT ecosystem value creation. The paper shows how IoT ecosystem actors may take the roles of Ideator, Designer, or Intermediary in different design layers, and, recommends this approach to better understand and describe ecosystem business models. Theoretical and managerial implications are discussed.
Anatomy of Viral Social Media Events

— Discussion topics go sometimes viral in social media without a seemingly coherent pattern. Existing literature shows these discussions can reach a very high level, but, notably, they prevail to varying degrees. This paper investigates the anatomy of viral social media events using a dataset of 960 viral social media discussion topics that have been identiﬁed by an algorithm from a variety of social media sources over two years’ time. A negative binomial regression shows that the average daily amount and the relative change in the daily amount of social media platforms at which the event has been discussed has a positive effect on the duration of the event. Average or relative amount of posts or authors has no or very little effect on event duration. The results suggest that viral social media events last longer when people using different social media platforms get exposed to them. This ﬁnding contributes to the literature on social media events, virality, and information diffusion.