Miracle-dz/UniFAR-FTUs huggingface dataset:
Hypotension in Subcortical Vascular Dementia, a New Risk Factor – Wasn’t It Hypertension?

The identification of additional genetic susceptibility genes in the etiology of AD and the metabolic mechanisms leading to differences in age of onset and disease pathogenesis are active areas of current susceptibility. Although all the contributing factors may never be known, scientists have identified several common threads. They include: age (more than 65 years old), sex (women are more likely than men are to develop the disease, in part because they live longer), toxicity (such as overexposure to certain trace metals, such as aluminum), head injury (serious traumatic injury to the head, for example, a concussion with a prolonged loss of consciousness) may be a risk factor for Alzheimer's), hormone replacement therapy (the exact role hormone replacement therapy may play in the development of dementia isn't yet clear; throughout the 1980s and '90s, evidence seemed to show that estrogen supplements given after menopause could reduce the risk of dementia; results from the large-scale Women's Health Initiative Memory Study indicated an increased risk of dementia for women taking estrogen after age 65: the verdict is not yet in on whether estrogen affects the risk of dementia if given at an earlier age), lifestyle (the same factors that put you at risk of heart disease, such as high blood pressure and high cholesterol, may also increase the likelihood that you'll develop Alzheimer's disease, poorly controlled diabetes is another risk factor). Atrial fibrillation, systolic hypertension, and angina have been associated with more rapid decline in cognition, while history of coronary artery bypass graft surgery, diabetes, and antihypertensive medications were associated with a slower rate of decline, and may represent modifiable risk factors for secondary prevention in Alzheimer disease. There was an age interaction such that systolic hypertension, angina, and myocardial infarction were associated with greater decline with increasing baseline age. The attenuated decline for diabetes and coronary artery bypass graft surgery may be due to selective survival. Some of these effects appear to vary with age (Mielke et al., 2007). There is an overlap of risk factors between VaD and AD, so much so that it raises some serious questions about vascular contributions to AD. Recognition that cerebrovascular disease causing dementia may be modified by treatment of cerebrovascular risk factors serves as an important tool for investigating various treatments aimed at secondary prevention of
MYOSITIS PURULENTA ACUTA CAUSED BY BACILLUS TYPHOSUS: REPORT OF A CASE

The pyogenic property of the typhoid bacillus was long a topic of discussion by medical writers. At present, as the result of satisfactory evidence, many authors agree that the typhoid bacillus can cause the formation of pus in various organs, although cases of typhoid followed by myositis purulenta acuta caused by the typhoid bacillus are very rare. Lately I have observed a case of myositis purulenta acuta of the upper arm caused by the typhoid bacillus during the course of typhoid fever. REPORT OF CASE History. —A man, aged 34, who had enjoyed good health, was suddenly taken ill with chills and fever, the temperature reaching 40.2 C. (104.3 F.) at onset. The lips were dry and the tongue was coated with a thick white fur; the appetite was poor; there was retraction of the abdominal wall, but no tenderness. At first there was slight diarrhea, but later, constipation. The
Impact du mode de recrutement des donneurs de sang sur la prévalence du VIH et du VHB à Bukavu, République démocratique du Congo

Objectives. To determine the impact of the mode of recruitment of blood donors on the prevalence of blood-borne infections (HIV and HBV). Methodology. Retrospective cohort study, conducted in Bukavu (eastern DR Congo) 2001-2005. HBsAg and HIV tests were analyzed according to age, sex, type, and category of donors. Proportions were compared with Pearson Chi2 or Fisher's exact tests and Chi2 trend tests, and the strength of associations measured by odds ratios (and their 95% CI). Results. Men accounted for 70.2% of the donors, and 88.3% were volunteers (n = 3292). Regular donors (n = 7442) provided 75% of the donations. The proportion of family donors decreased over time, from 14.3% in 2001 to 5.1% in 2005. HIV prevalence was 1% and that of HBsAg 3.7%. Prevalence rates were higher among new donors than among regular donors (HIV 1.9% versus 0.2% and HBsAg 7.3% versus 0.5%), among family donors than among volunteers (4.2% versus 1.6% for HIV and 9.9% versus 7% for HBs Ag, and among women than among men (2.8% versus 1.6%, OR = 1.79 [1.08-2.96]). Thus new women family donors were 3.75 times more likely to be HIV-positive as new volunteers who were women (OR = 3.75 [1.65-8.55]). The prevalence of HBsAg among new women donors was 5.8%, lower than among their male counterparts, 7.9% (OR = 0.71 [0.51-0.98]). Conclusion. Risk of contamination by seropositive donors was lowest for regular and volunteer blood donors.
Bridging Information Security and Environmental Criminology Research to Better Mitigate Cybercrime

Cybercrime is a complex phenomenon that spans both technical and human aspects. As such, two disjoint areas have been studying the problem from separate angles: the information security community and the environmental criminology one. Despite the large body of work produced by these communities in the past years, the two research efforts have largely remained disjoint, with researchers on one side not benefitting from the advancements proposed by the other. In this paper, we argue that it would be beneficial for the information security community to look at the theories and systematic frameworks developed in environmental criminology to develop better mitigations against cybercrime. To this end, we provide an overview of the research from environmental criminology and how it has been applied to cybercrime. We then survey some of the research proposed in the information security domain, drawing explicit parallels between the proposed mitigations and environmental criminology theories, and presenting some examples of new mitigations against cybercrime. Finally, we discuss the concept of cyberplaces and propose a framework in order to define them. We discuss this as a potential research direction, taking into account both fields of research, in the hope of broadening interdisciplinary efforts in cybercrime research
Acoustic Scene Classification Based on a Large-margin Factorized CNN

In this paper, we present an acoustic scene classification framework based on a large-margin factorized convolutional neural network (CNN). We adopt the factorized CNN to learn the patterns in the time-frequency domain by factorizing the 2D kernel into two separate 1D kernels. The factorized kernel leads to learn the main component of two patterns: the long-term ambient and short-term event sounds which are the key patterns of the audio scene classification. In training our model, we consider the loss function based on the triplet sampling such that the same audio scene samples from different environments are minimized, and simultaneously the different audio scene samples are maximized. With this loss function, the samples from the same audio scene are clustered independently of the environment, and thus we can get the classifier with better generalization ability in an unseen environment. We evaluated our audio scene classification framework using the dataset of the DCASE challenge 2019 task1A. Experimental results show that the proposed algorithm improves the performance of the baseline network and reduces the number of parameters to one third. Furthermore, the performance gain is higher on unseen data, and it shows that the proposed algorithm has better generalization ability.
RecSplit: Minimal Perfect Hashing via Recursive Splitting

A minimal perfect hash function bijectively maps a key set $S$ out of a universe $U$ into the first $|S|$ natural numbers. Minimal perfect hash functions are used, for example, to map irregularly-shaped keys, such as string, in a compact space so that metadata can then be simply stored in an array. While it is known that just $1.44$ bits per key are necessary to store a minimal perfect function, no published technique can go below $2$ bits per key in practice. We propose a new technique for storing minimal perfect hash functions with expected linear construction time and expected constant lookup time that makes it possible to build for the first time, for example, structures which need $1.56$ bits per key, that is, within $8.3$% of the lower bound, in less than $2$ ms per key. We show that instances of our construction are able to simultaneously beat the construction time, space usage and lookup time of the state-of-the-art data structure reaching $2$ bits per key. Moreover, we provide parameter choices giving structures which are competitive with alternative, larger-size data structures in terms of space and lookup time. The construction of our data structures can be easily parallelized or mapped on distributed computational units (e.g., within the MapReduce framework), and structures larger than the available RAM can be directly built in mass storage.
Mapping Supervised Bilingual Word Embeddings from English to low-resource languages

It is very challenging to work with low-resource languages due to the inadequate availability of data. Using a dictionary to map independently trained word embeddings into a shared vector space has proved to be very useful in learning bilingual embeddings in the past. Here we have tried to map individual embeddings of words in English and their corresponding translated words in low-resource languages like Estonian, Slovenian, Slovakian, and Hungarian. We have used a supervised learning approach. We report accuracy scores through various retrieval strategies which show that it is possible to approach challenging tasks in Natural Language Processing like machine translation for such languages, provided that we have at least some amount of proper bilingual data. We also conclude that we can follow an unsupervised learning path on monolingual text data as that is more suitable for low-resource languages.
Contrarian effects and echo chamber formation in opinion dynamics

The relationship between the topology of a network and specific types of dynamics unfolding in networks constitutes a subject of substantial interest. One type of dynamics that has attracted increasing attention because of its several potential implications is opinion formation. A phenomenon of particular importance, known to take place in opinion formation, is echo chambers’ appearance. In the present work, we approach this phenomenon, while emphasizing the influence of contrarian opinions in a multi-opinion scenario. To define the contrarian opinion, we considered the underdog effect, which is the eventual tendency of people to support the less popular option. We also considered an adaptation of the Sznajd dynamics with the possibility of friendship rewiring, performed on several network models. We analyze the relationship between topology and opinion dynamics by considering two measurements: opinion diversity and network modularity. Two specific situations have been addressed: (i) the agents can reconnect only with others sharing the same opinion; and (ii) same as in the previous case, but with the agents reconnecting only within a limited neighborhood. This choice can be justified because, in general, friendship is a transitive property along with subsequent neighborhoods (e.g., two friends of a person tend to know each other). As the main results, we found that the underdog effect, if strong enough, can balance the agents’ opinions. On the other hand, this effect decreases the possibilities of echo chamber formation. We also found that the restricted reconnection case reduced the chances of echo chamber formation and led to smaller echo chambers.
DeepVS: An Efficient and Generic Approach for Source Code Modeling Usage

The source code suggestions provided by current IDEs are mostly dependent on static type learning. These suggestions often end up proposing irrelevant suggestions for a peculiar context. Recently, deep learning-based approaches have shown great potential in the modeling of source code for various software engineering tasks. However, these techniques lack adequate generalization and resistance to acclimate the use of such models in a real-world software development environment. This letter presents \textit{DeepVS}, an end-to-end deep neural code completion tool that learns from existing codebases by exploiting the bidirectional Gated Recurrent Unit (BiGRU) neural net. The proposed tool is capable of providing source code suggestions instantly in an IDE by using pre-trained BiGRU neural net. The evaluation of this work is two-fold, quantitative and qualitative. Through extensive evaluation on ten real-world open-source software systems, the proposed method shows significant performance enhancement and its practicality. Moreover, the results also suggest that \textit{DeepVS} tool is capable of suggesting zero-day (unseen) code tokens by learning coding patterns from real-world software systems.
Fever of unknown origin in children: A challenge persisting with advancing medical care

Abstract Although huge advances have been made in the field of medicine, fever of unknown origin (FUO) continues to be a significant health problem and an important cause of morbidity and mortality, especially in children. The aim of this study was to study current spectrum of FUO, newly emerging challenges and outcome of FUO. A prospective observational study was conducted over a 16 month period (May 2012-September 2013). 53 children aged 4 months to 15 years met the definition of FUO and were included. Children with known immunodeficiency disorders or other chronic disorders were excluded. A diagnosis was reached in 47 (88.7%) patients. Infections were the commonest cause accounting for FUO in 37 (69.8%) patients. Haematological disorders were found in 8 (15%) and autoimmune diseases in 2 (3.8%) patients. Among infections, the most common causes of FUO were tuberculosis (TB) (37.8%), enteric fever (29.7%), Epstein-Barr virus (EBV) (8.1%) and brucellosis (8.1%). TB was extra-pulmonary in 11 cases and pulmonary in 3 cases. Amongst the haematological disorders, 3 patients had haemophagocytic lymphohistiocytosis (HLH), 3 had leukemia, 1 had non-Hodgkin lymphoma and 1 had autoimmune lymphoproliferative syndrome. Juvenile idiopathic arthritis with systemic onset and polyarteritis nodosa accounted for the two cases of autoimmune disease. Elevated C-reactive protein (CRP) levels were associated with an infectious etiology. Bone tenderness, thrombocytopenia and neutropenia predicted haematological malignancy. 1 patient of HLH died of complications during initial hospitalization and 3 other patients (1 HIV, 2 TB) died on follow up. TB, especially extrapulmonary, and enteric fever are still significant public health problems and were the commonest causes of FUO in our population. Due to advances in diagnostic facilities, some diseases like urinary tract infection (UTI) and hepatitis have become less common; however, other diseases like EBV have become more common causes of FUO. HLH is emerging as a significant cause of morbidity and mortality in FUO patients.
A Novel Sensorised Insole for Sensing Feet Pressure Distributions

Wearable sensors are gaining in popularity because they enable outdoor experimental monitoring. This paper presents a cost-effective sensorised insole based on a mesh of tactile capacitive sensors. Each sensor’s spatial resolution is about 4 taxels/cm2 in order to have an accurate reconstruction of the contact pressure distribution. As a consequence, the insole provides information such as contact forces, moments, and centre of pressure. To retrieve this information, a calibration technique that fuses measurements from a vacuum chamber and shoes equipped with force/torque sensors is proposed. The validation analysis shows that the best performance achieved a root mean square error (RMSE) of about 7 N for the contact forces and 2 Nm for the contact moments when using the force/torque shoe data as ground truth. Thus, the insole may be an alternative to force/torque sensors for certain applications, with a considerably more cost-effective and less invasive hardware.
How to eliminate detour behaviors in E-hailing: On-line detection and Pricing regulation

With the fast development of information and communication technology (ICT), taxi business becomes a typical electronic commerce mode. However, one traditional problem still exists in taxi service, that greedy taxi drivers may deliberately take unnecessary detours to overcharge passengers. The detection of these fraudulent behaviors is essential to ensure high-quality taxi service. In this paper, we propose a novel framework for detecting and analyzing the detour misbehaviors both in off-line database and among on-line trips. Applying our framework to real-world taxi data, a remarkable performance (AUC > 0:98, 100% of detour trajectories can be detected at less than 10% false alarm rate) has been achieved in off-line phases, meanwhile, an excellent precision (AUC > 0:9) also has arrived in on-line detection. In additional, some constructive suggestions upon pricing regulation are also provided to control the happening of detours. Finally, some commercial value-added applications in DiDi benefited from our method have yielded good results to improve the map service.
Hydra: A Multiple Blockchain Protocol for Improving Transaction Throughput

Improving transaction throughput is one of the main challenges in decentralized payment systems. Attempts to improve transaction throughput in cryptocurrencies are usually a trade-off between throughput and security or introduce a central component. We propose Hydra, a decentralized protocol that improves transaction throughput without the security trade-off and has no central component. Our novel approach distributes blocks over multiple blockchains. Hydra makes a trade-off between transaction throughput and finality, the time it takes to stabilize the record of a transaction in the blockchain. We rigorously analyze the double spend attack in a multiple-blockchain protocol. Our analysis shows that the number of transactions per second can be increased significantly while finality is within acceptable boundaries.
Capture of interstellar objects: a source of long-period comets

We simulate the passage through the Sun–Jupiter system of interstellar objects (ISOs) similar to 1I/‘Oumuamua or 2I/Borisov. Capture of such objects is rare and overwhelmingly from low incoming speeds on to orbits akin to those of known long-period comets. This suggests that some of these comets could be of extrasolar origin, in particular inactive ones. Assuming ISOs follow the local stellar velocity distribution, we infer a volume capture rate of $0.051\, \mathrm{au}^3\, \mathrm{yr}^{-1}$. Current estimates for orbital lifetimes and space densities then imply steady-state captured populations of ∼102 comets and ∼105 ‘Oumuamua-like rocks, of which 0.033 per cent are within 6 au at any time.
Modern Medicine and the 20th Century Decline in Mortality: Evidence on the Impact of Sulfa Drugs

Previous research suggests that medical advances played a negligible role in the large decline in mortality rates during the first half of the twentieth century. This paper, in contrast, presents evidence that sulfa drugs―the first pharmaceuticals effective at treating infectious diseases― were an important cause of U.S. mortality declines after their discovery in the 1930s. Using timeseries and difference-in-difference methods (with infectious diseases unaffected by sulfa drugs as a comparison group), we present evidence on the effects of sulfa drugs on mortality. We find that sulfa drugs led to a 25% decline in maternal mortality, a 13% decline in pneumonia and influenza mortality, and a 52% decline in scarlet fever mortality between 1937 and 1943. Sulfa drugs also widened racial disparities in mortality, suggesting that new medical technology diffuses more rapidly among whites than blacks and consistent with the hypothesis that innovation initially increases inequality across population subgroups.
Stress effects on fundamental frequency of human voice: a review

The work describes the effect of stress on voice parameters. The human voice is a difficult signal to analyse because it changes much over time and is complex in nature. The fundamental frequency is an important parameter of voice and is considered to be one of the most important features to characterise speech and speaker-specific patterns. Stress analysis and voice disease diagnostics essentially require the measurement and analysis of the fundamental frequency of human voice and after that we can take necessary steps for healthcare management.
Intensity of Case Management Services

Abstract Specialized programs for pregnant, drug dependent women have assisted many in achieving abstinence during pregnancy. Following delivery, however, such women often resume drug use and drop out of treatment, placing their children at even greater risk for subsequent medical and developmental problems. Standard outreach services, while generally effective as a public health measure for high-risk populations of women and children, are often insufficient for chronic and severely drug dependent women. The present study was a randomized clinical trial comparing maternal and infant outcomes for drug dependent women assigned to either routine or intensified case management services for the first 4 months following delivery. Women randomly assigned to intensified case management showed better treatment retention, accessed a greater variety of services, were more likely to be abstinent from cocaine at 4-month follow-up, and felt their children received greater benefit from the services than women assigned to routine case management. The number of case management visits was positively correlated with total time in treatment across both intervention groups. Study findings support the efficacy of intensified case management services for drug dependent women and their children.
Hospital Treatment Practices, 30-Day Hospital Readmissions, and Long-Term Prognosis in Patients Hospitalized with Acute Myocardial Infarction: A Dissertation

The signature of the Dean of the Graduate School of Biomedical Sciences signifies that the student has met all graduation requirements of the school. DEDICATION This dissertation is dedicated to my beloved family whose support and belief in me never wavered on this journey. ACKNOWLEDGEMENTS In this way, I would like to thank all the people who have helped and supported me during my doctoral training at the University of Massachusetts Medical School. I would like to express my sincere gratitude to my mentor, Dr. Robert Goldberg, for his thorough guidance, constant encouragement and altruistic support all these years. This work would never have been possible without his thoughtful insights and direction which has ultimately made me a better researcher and writer. I am grateful to my committee members, Drs. Charles Eaton, for their valuable suggestions and comments. I would also like to thank members of the Worcester Heart Attack Study for their support and help. The faculty of the Clinical & Population Health Research program has provided me a tremendous graduate education and remarkable research training. I would like to thank the faculty and administrative staff of the Department of Quantitative Health Sciences for their immeasurable help during my time at the school. Finally, I want to thank my fellow classmates and my friends here and in Taiwan for their support and encouragement. ABSTRACT Background