Miracle-dz/UniFAR-FTUs huggingface dataset:
INNOVATION ECOSYSTEMS AND THE SUCCESS OF EARLY MOVERS IN TECHNOLOGY TRANSITIONS: EVIDENCE FROM THE SEMICONDUCTOR LITHOGRAPHY EQUIPMENT INDUSTRY, 1962-2004.

We examine how external innovation challenges, apart from a focal firm’s own internal innovation challenges, affect market outcomes. We label these external innovation challenges as a firm’s ‘innovation ecosystem’ and distinguish between component challenges, whose resolution depends on the efforts of upstream suppliers whose outputs are bundled by the focal firm, and complement challenges, whose resolution depends on the efforts of downstream complementors whose outputs are bundled by the focal firm’s customers. We examine these issues across nine technology transitions in the semiconductor lithography equipment industry from its emergence in 1962 to 2004. We find that ecosystem challenges have an important effect. However, because of opposing effects of complexity in components and complexity in complements on the existence of early mover advantages, the impact of ecosystems on firm performance can only be uncovered by separating the roles of these underlying elements. We find that early mover advantage in a new technology generation is enhanced when component development challenges are high. However, early mover advantage is eroded when the complement development challenges are high. Indeed, we find that when the component challenge is low and the complement challenge is high, early movers face significant disadvantages. The findings of this study argue that strategic analysis in regimes of environmental change need to extend beyond traditional firm boundaries or firm-customer dyad to encompass the broader ecosystem on which firms rely.
GPU Implementation of Friend Recommendation System using CUDA for Social Networking Services

Social networking services (SNSs) provide a platform where likeminded people interact and express opinions. The trends of socializing have changed drastically and the general population is turning to these services to socialize and network with new people. Massive infrastructure compliments uninterrupted usage of these services. Owing to the rapidly growing user base of SNSs, there is always a need to improve upon the existing infrastructure to keep cost and performance in tune with one another. GPUs are proving to be a viable solution to bridge the gap between the two. In this paper we describe GPU implementation of a Friend recommender system which is based on content-based filtering mechanism. It has given significant speed ups from its previous counterparts, thus making the whole process more efficient.
Numerous recursive sites contribute to accuracy of splicing of Numerous recursive sites contribute to accuracy of splicing of long introns in flies [preprint] long introns in flies [preprint] us know how access to this document benefits you.

Recursive splicing, a process by which a single intron is removed from pre-mRNA transcripts in multiple distinct segments, has been observed in a small subset of Drosophila melanogaster introns. However, detection of recursive splicing requires observation of splicing intermediates which are inherently unstable, making it difficult to study. Here we developed new computational approaches to identify recursively spliced introns and applied them, in combination with existing methods, to nascent RNA sequencing data from Drosophila S2 cells. These approaches identified hundreds of novel sites of recursive splicing, expanding the catalog of recursively spliced fly introns by 4-fold. Recursive sites occur in most very long (> 40 kb) fly introns, including many genes involved in morphogenesis and development, and tend to occur near the midpoints of introns. Suggesting a possible function for recursive splicing, we observe that fly introns with recursive sites are spliced more accurately than comparably sized non-recursive introns.
Telephone Directories as Sampling Frames

Of 1000 respondents in a face-to-face survey, 22% did not live in households listed in telephone directories, and therefore could not have been included in a sample using telephone directories as a sampling frame. Those not listed were significantly younger, more likely to be never married, separated, or divorced, and were more likely to live in the northern part of New Zealand.
Enhancing the process of diesel engine condition monitoring

Condition monitoring technology for diesel engines has advanced at a rapid pace in recent years. Diesel engine manufacturers and third-party vendors have developed techniques that make it possible to determine the mechanical condition and performance of operating diesel engines. Such systems apply microprocessor-based instrumentation and computer analysis software to quantify engine combustion characteristics, valve events, piston motion, cylinder and liner condition, as well as auxiliary equipment such as turbochargers, pumps and motors. Non-intrusive measurement techniques provide time-domain, frequency-domain and process related data that are used to infer existing or impending problems and detect deviations from normal or achievable performance. A challenge industry faces is how to use the large amounts of data being produced by these programs to maximize the availability, reliability and ultimately, the economic performance of their equipment. This paper discusses methods for enhancing the analysis process to advance a diesel engine condition monitoring program. The physical aspects of combustion characteristics of compression-ignition engines are crucial performance indicators and are covered in depth using actual cylinder pressure and vibration signatures. Sophisticated analysis techniques and data-reduction schemes produce normalized measures that are trendable and can automate the analysis process. Case studies provided by Commonwealth Edison Company are used tomore » illustrate the benefits of employing a state-of-the-art condition monitoring program. The paper will also illustrate how such programs are used to detect specific failure modes and recognize strategies for improving the overall performance of diesel engines. « less
Tracking wrist motion to detect and measure the eating intake of free-living humans

This dissertation is motivated by the growing prevalence of obesity, a health problem currently affecting over 500 million people worldwide. It is composed of two studies. In the first study, a new method is developed to detect how many bites a person takes during a meal in real time. A pattern has been found that the wrist of a person undergoes a characteristic roll motion as food is picked up and placed into the mouth. This motion can be tracked by a gyroscope sensor placed on the wrist. This work could be used in many weight loss and obesity treatment applications, including monitoring intake, slowing eating rate, and providing a cue for mindful eating. In the second study, a new method is developed to automatically distinguish eating activity from other activities in natural daily living. Accelerometers are used to detect the typical burst activity at the beginning and the end of each eating activity and gyroscope roll motion features are used during hypothesized detections to differentiate eating activities from other activities. This work has many potential applications. It could be used by individuals for self-monitoring for weight loss and weight maintenance. It could be combined with a food diary, 24-hour recall or food frequency questionnaire to improve compliance and accuracy in measuring consumption. The two methods could potentially be combined to automatically count bites of intake all day. The methods could also be used by clinical practitioners to monitor the eating patterns of patients (for example during diabetes treatment), or by researchers in epidemiological and genetic studies (for example in studies of the physical activity or eating habits of specific demographics).
HIV/AIDS Associated Lymphoma: Review

Abstract Lymphoma is one of the hematologic malignancies that occur at a higher rate in human immunodeficiency virus-infected individuals. It is one of the most frequent neoplastic causes of death in those individuals. Non-Hodgkin’s lymphoma and Hodgkin’s lymphomas are acquired immunodeficiency syndrome defining lymphoma and non-acquired immunodeficiency syndrome defining lymphoma, respectively. Non-Hodgkin’s lymphoma is the most common type of lymphoma in human immunodeficiency virus-positive people. The lymphoma that develops in patients infected with the human immunodeficiency virus/acquired immunodeficiency syndrome is heterogeneous in terms of morphology, pathogenesis pathways, and cellular derivation. A narrative review was conducted on the basis of relevant literature on the current topic to summarize the current epidemiology, pathogenesis, laboratory diagnosis, and treatment of lymphoma in human immunodeficiency virus-infected patients. The finding showed that although the incidence of non-Hodgkin’s lymphoma has decreased after the advent of highly active antiretroviral therapy, it has remained higher in human immunodeficiency virus-infected people than in the general population. On the other hand, the incidence of Hodgkin’s lymphoma has increased after the introduction of highly active antiretroviral therapy. Therefore, it is recommended that people living with human immunodeficiency virus/ acquired immunodeficiency syndrome be screened for the development of lymphoma to increase their survival time and quality of life, and further research is required regarding the pathogenesis, treatment, and laboratory diagnosis of human immunodeficiency virus/ acquired immunodeficiency syndrome-associated lymphoma.
Folic Acid and Chitosan-Functionalized Gold Nanorods and Triangular Silver Nanoplates for the Delivery of Anticancer Agents

Background Advances in the field of nanotechnology have shed light on the applications of nanoparticles for cancer treatment. Methods Folic acid and chitosan-functionalized gold nanorods (FACS-R) and triangular silver nanoplates (FACS-T) were synthesized and their properties were elucidated by UV-visible spectrophotometry, Fourier-transform infrared spectroscopy, field emission transmission electron microscopy and high-resolution X-ray diffraction. Results The average size of the FACS-R was determined to be a transverse length of 13.1 ± 1.8 nm and a longitudinal length of 47.2 ± 8.9 nm with an aspect ratio of 3.6. The average size of FACS-T was measured to be 31.8 ± 7.7 nm. Colloidal solutions of FACS-R and FACS-T were stable on the shelf at ambient temperature for 14 days in the dark. Anticancer agents were encapsulated in FACS-R and FACS-T. FACS-T showed a higher encapsulation efficiency with docetaxel, paclitaxel and diallyl disulfide than FACS-R. The cell viability on human gastric adenocarcinoma cells (AGS), human epithelial cervix adenocarcinoma cells (HeLa) and human colorectal adenocarcinoma cells (HT-29) after treatment with anticancer agent-encapsulated FACS-R and FACS-T was determined using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Interestingly, paclitaxel-encapsulated FACS-R and FACS-T showed the highest percentages of early and late apoptosis on HeLa cells. A cell cycle analysis demonstrated increased G2/M arrest on HeLa cells with docetaxel and paclitaxel-encapsulated FACS-R and FACS-T. The FACS-T induced more G2/M arrest on HeLa cells than the FACS-R. To assess applications in near-infrared photothermal therapy (PTT), the cell viability on HeLa cells with the anticancer agent-encapsulated FACS-R and FACS-T was assessed in the presence or absence of 808 nm laser irradiation. The results showed that 808 nm laser irradiation significantly decreased cell viability. Conclusion Collectively, the triangular silver nanoplates were more effective than the gold nanorods for PTT. We believe that as-prepared nanoparticles have remarkable features and will become promising future nanomedicine.
A Practical Approach to Severity Classification and Treatment of Dry Eye Disease: A Proposal from the Mexican Dry Eye Disease Expert Panel

Abstract Dry eye disease (DED) has a higher prevalence than many important systemic disorders like cardiovascular disease and diabetes mellitus, representing a significant quality of life burden for the affected patients. It is a common reason for consultation in general eye clinics worldwide. Nowadays, the diagnostic and therapeutic approach at the high corneal and ocular surface specialty level should be reserved for cases of severe and chronic dry eye disease associated with systemic autoimmune diseases or complicated corneal and ocular surface pathologies. In such cases, the diagnostic and therapeutic approach is often complex, elaborate, time-consuming, and costly due to the use of extensive dry eye questionnaires, noninvasive electronic diagnostic equipment, and clinical laboratory and ancillary tests. However, other eye care specialists attend a fair amount of DED cases; therefore, its diagnosis, classification, and management should be simple, practical, achievable, and effective. Considering that many patients attending non-specialized dry eye clinics would benefit from better ophthalmological attention, we decided to elaborate a practical DED classification system based on disease severity to help clinicians discriminate cases needing referral to subspecialty clinics from those they could attend. Additionally, we propose a systematic management approach and general management considerations to improve patients’ therapeutic outcomes according to disease severity.
A WeChat-Based Rehabilitation Platform for Children and Adolescents with Congenital Heart Disease to Promote Cardiac FITness (HeartFIT): Protocol for a Mixed-Methods Strategy from Evidence-Based Design to Pilot Study

Abstract Progress in medical and surgical care has tremendously improved the survival rates of children with congenital heart disease (CHD). However, reduced aerobic capacity and health-related issues remain a threaten to quality survival and prevention of related complications among children and adolescents with CHD. This research program aims to develop and evaluate a WeChat-based health platform (HeartFIT) to facilitate cardiac rehabilitation and promote physical fitness for this rapidly expanding young population. The study protocol describes the use of an iterative process of using a mixed-methods strategy to develop, refine, and pilot test the proposed HeartFIT platform. A sequential problem-solving process comprising four iterative phases with ongoing end-user input will be implemented. In phase 1, relevant literature was systematically reviewed (completed) and then child-parent dyads will be interviewed to understand the broad context and the requirements and considerations of the target population toward the WeChat-based rehabilitation platform. In phase 2, key features and priority functionalities for the platform will be ideated and refined, and a digital interactive prototype will be created. In phase 3, heuristic evaluation and three rounds of end-user testing will be conducted to ensure further refinement and usability of the prototype. In phase 4, a prospective pilot study will be performed to investigate the feasibility, acceptability, and preliminary efficacy of the developed platform over a 12-week intervention period. If HeartFIT intervention is feasible, acceptable, and demonstrates promising efficacy, an adequately powered randomized controlled trial (future work) will be deployed to test the real-world effectiveness of the intervention.
Towards Maximizing a Perceptual Sweet Spot

The sweet spot can be interpreted as the region where acoustic sources create a spatial auditory illusion. We study the problem of maximizing this sweet spot when reproducing a desired sound wave using an array of loudspeakers. To achieve this, we introduce a theoretical framework for spatial sound perception that can be used to define a sweet spot, and we develop a method that aims to generate a sound wave that directly maximizes the sweet spot defined by a model within this framework. Our method aims to incorporate perceptual principles from the onset and is flexible: while it imposes little to no constraints on the regions of interest, the arrangement of loudspeakers or their radiation pattern, it allows for audio perception models that include state-of-the-art monaural perceptual models. Proof-of-concept experiments show that our method outperforms state-of-the-art methods when comparing them in terms of their localization and coloration properties.
Several Proofs of Coerciveness of First-Order System Least-Squares Methods for General Second-Order Elliptic PDEs

In this paper, we present proofs of the coerciveness of first-order system least-squares methods for general (possibly indefinite) second-order linear elliptic PDEs under a minimal uniqueness assumption. For general linear second-order elliptic PDEs, the uniqueness, existence, and well-posedness are equivalent due to the compactness of the operator and Fredholm alternative. Thus only a minimal uniqueness assumption is assumed: the homogeneous equation has a unique zero solution. The coerciveness of the standard variational problem is not required. The paper's main contribution is our first proof, which is a straightforward and short proof using the inf-sup stability of the standard variational formulation. The proof can potentially be applied to other equations or settings once having the standard formulation's stability. We also present two other proofs for the least-squares methods of general second-order linear elliptic PDEs. The second proof is based on a lemma introduced in the discontinuous Petrov-Galerkin method, and the third proof is based on various stability analyses of the decomposed problems. As an application, we also discuss least-squares finite element methods for problems with a nonsingular $H^{-1}$ right-hand side.
Uncertainty Estimation of Pedestrian Future Trajectory Using Bayesian Approximation

Past research on pedestrian trajectory forecasting mainly focused on deterministic predictions which provide only point estimates of future states. These future estimates can help an autonomous vehicle plan its trajectory and avoid collision. However, under dynamic traffic scenarios, planning based on deterministic predictions is not trustworthy. Rather, estimating the uncertainty associated with the predicted states with certain level of confidence can lead to robust path planning. Hence, the authors propose to quantify this uncertainty during forecasting using stochastic approximation which deterministic approaches fail to capture. The current method is simple and applies Bayesian approximation during inference to standard neural network architectures for estimating uncertainty. The authors compared the predictions between the probabilistic neural network (NN) models with the standard deterministic models. The results indicate that the mean predicted path of probabilistic models was closer to the ground truth when compared with the deterministic prediction. Further, the effect of stochastic dropout of weights and long-term prediction on future state uncertainty has been studied. It was found that the probabilistic models produced better performance metrics like average displacement error (ADE) and final displacement error (FDE). Finally, the study has been extended to multiple datasets providing a comprehensive comparison for each model.
Many-fermion simulation from the contracted quantum eigensolver without fermionic encoding of the wave function

Quantum computers potentially have an exponential advantage over classical computers for the quantum simulation of many-fermion quantum systems. Nonetheless, fermions are more expensive to simulate than bosons due to the fermionic encoding -- a mapping by which the qubits are encoded with fermion statistics. Here we generalize the contracted quantum eigensolver (CQE) to avoid fermionic encoding of the wave function. In contrast to the variational quantum eigensolver, the CQE solves for a many-fermion stationary state by minimizing the contraction (projection) of the Schr\"odinger equation onto two fermions. We avoid fermionic encoding of the wave function by contracting the Schr\"odinger equation onto an unencoded pair of particles. Solution of the resulting contracted equation by a series of unencoded two-body exponential transformations generates an unencoded wave function from which the energy and two-fermion reduced density matrix (2-RDM) can be computed. We apply the unencoded and the encoded CQE algorithms to the hydrogen fluoride molecule, the dissociation of oxygen O$_{2}$, and a series of hydrogen chains. Both algorithms show comparable convergence towards the exact ground-state energies and 2-RDMs, but the unencoded algorithm has computational advantages in terms of state preparation and tomography.
UCL-Dehaze: Toward Real-World Image Dehazing via Unsupervised Contrastive Learning

While the wisdom of training an image dehazing model on synthetic hazy data can alleviate the difficulty of collecting real-world hazy/clean image pairs, it brings the well-known domain shift problem. From a different yet new perspective, this paper explores contrastive learning with an adversarial training effort to leverage unpaired real-world hazy and clean images, thus alleviating the domain shift problem and enhancing the network’s generalization ability in real-world scenarios. We propose an effective unsupervised contrastive learning paradigm for image dehazing, dubbed UCL-Dehaze. Unpaired real-world clean and hazy images are easily captured, and will serve as the important positive and negative samples respectively when training our UCL-Dehaze network. To train the network more effectively, we formulate a new self-contrastive perceptual loss function, which encourages the restored images to approach the positive samples and keep away from the negative samples in the embedding space. Besides the overall network architecture of UCL-Dehaze, adversarial training is utilized to align the distributions between the positive samples and the dehazed images. Compared with recent image dehazing works, UCL-Dehaze does not require paired data during training and utilizes unpaired positive/negative data to better enhance the dehazing performance. We conduct comprehensive experiments to evaluate our UCL-Dehaze and demonstrate its superiority over the state-of-the-arts, even only 1,800 unpaired real-world images are used to train our network. Source code is publicly available at https://github.com/yz-wang/UCL-Dehaze.
The limitations of the theoretical analysis of applied algorithms

The theoretical analysis of performance has been an important tool in the engineering of algorithms in many application domains. Its goals are to predict the empirical performance of an algorithm and to be a yardstick that drives the design of novel algorithms that perform well in practice. While these goals have been achieved in many instances, they have not been achieved in some other crucial application domains. In this paper, I focus on the example of sequencing bioinformatics, an inter-disciplinary ﬁeld that uses algorithms to extract biological meaning from genome sequencing data. I will demonstrate two concrete examples of how theoretical analysis has failed to achieve its goals but also give one encouraging example of success. I will then catalog some of the challenges of applying theoretical analysis to sequencing bioinformatics, argue why empirical analysis is not enough, and give a vision for improving the relevance of theoretical analysis to sequencing bioinformatics and other application domains. By recognizing the problem, understanding its roots, and providing potential solutions, this work can hopefully be a crucial ﬁrst step towards making theoretical analysis more relevant in modern application domains.