Miracle-dz/UniFAR-FTUs huggingface dataset:
Internet use by primary care patients: where is the digital divide?

BACKGROUND AND OBJECTIVES Internet-based technologies such as personal health records and patient portals are increasingly viewed as essential for enhancing patient-provider communication and patient-centered care. We examined how primary care patients use the Internet, particularly patient characteristics associated with Internet use. METHODS We surveyed patients in five primary care clinic waiting rooms. Patients who had used email or the Internet in the past month (Internet users) were asked how often they used a computer for a variety of tasks. Participants who reported not using the Internet were asked about several potential barriers to Internet use. RESULTS We approached 713 patients, and 638 (89.6%) completed questionnaires; 499 (78%) were Internet users and 139 (22%) were non-users. Lack of computer access and not knowing how to use email or the Internet were the most common barriers to Internet use. Younger age, higher education and income, better health, and absence of a chronic illness were associated with Internet use. After controlling for age and other variables, chronic illness was no longer associated with Internet use. CONCLUSIONS Internet use was high among our primary care patients. The major factor associated with Internet use among patients with chronic conditions was their age. If older adults with chronic illness are to reap the benefits of health information technology, their Internet access will need to be improved. Institutions that are planning to offer consumer health information technology should be aware of groups with lower Internet access.
Dating of Neogene igneous rocks in the Halmahera region: arc initiation and development

Abstract Potassium-argon ages of Neogene to Recent igneous rocks from the Halmahera region record a history of intra-oceanic arc development since the late Middle Miocene following an earlier phase of collisional plutonism. Arc formation from the Middle Miocene onwards was due to the east-directed subduction of the Molucca Sea plate beneath the Philippine Sea plate as it arrived at the Eurasian margin. The distribution of ages within the Neogene arc indicates a northward migration of volcanic activity during the Late Miocene to Pliocene. Results of the dating work show that after collision with the Australian margin at c. 22 Ma there was a period of volcanic quiescence and limestone deposition before a new arc formed. This arc began erupting at around 11 Ma on Obi as a result of subduction of the Molucca Sea plate. Initiation of subduction is thought to have occurred around 15–17 Ma and may have been responsible for disturbing potassium-argon ages of pre-Neogene rocks. Dates from fresh rocks show that the volcanic front migrated northwards through Bacan and Halmahera throughout the Late Miocene to Early Pliocene. Limestone deposition was curtailed as arc activity migrated north while volcanism died out from the south. No Neogene volcanism younger than 8 Ma is observed in the Obi area while on Bacan subduction-related volcanism ceased at c. 2 Ma. Late Pliocene crustal deformation caused a 30–40 km westward shift of the volcanic front. Quaternary volcanic rocks exposed in Bacan and the extreme south of Halmahera are not direct products of subduction but, rather, display geochemical characteristics of both subduction and fault-related magmatism. These volcanic rocks are distributed along splays of the Sorong fault system. The formation and propagation of the Halmahera arc is a consequence of the clockwise rotation of the Philippine Sea plate as the southern edge moved across the northern Australian margin and impinged on the east Eurasian margin. The ages of initiation of volcanism and subduction track the developing plate boundary as subduction propagated northwards.
Grammar guided genetic programming for multiple instance learning: an experimental study

This paper introduces a new Grammar-Guided Genetic Programming algorithm for solving multi-instance Learning problems. This algorithm, called G3P-MI, is evaluated and compared with other Multi-Instance classification techniques on different application domains. Computational experiments show that the G3P-MI often obtains consistently better results than other algorithms in terms of accuracy, sensitivity and specificity. Moreover, it adds comprehensibility and clarity into the knowledge discovery process, expressing the information in the form of IF-THEN rules. Our results confirm that evolutionary algorithms are appropriate for dealing with multi-instance learning problems.
Novel Arsenic Nanoparticles Are More Effective and Less Toxic than As (III) to Inhibit Extracellular and Intracellular Proliferation of Leishmania donovani

Visceral leishmaniasis, a vector-borne tropical disease that is threatening about 350 million people worldwide, is caused by the protozoan parasite Leishmania donovani. Metalloids like arsenic and antimony have been used to treat diseases like leishmaniasis caused by the kinetoplastid parasites. Arsenic (III) at a relatively higher concentration (30 μg/mL) has been shown to have antileishmanial activity, but this concentration is reported to be toxic in several experimental mammalian systems. Nanosized metal (0) particles have been shown to be more effective than their higher oxidation state forms. There is no information so far regarding arsenic nanoparticles (As-NPs) as an antileishmanial agent. We have tested the antileishmanial properties of the As-NPs, developed for the first time in our laboratory. As-NPs inhibited the in vitro growth, oxygen consumption, infectivity, and intramacrophage proliferation of L. donovani parasites at a concentration which is about several fold lower than that of As (III). Moreover, this antileishmanial activity has comparatively less cytotoxic effect on the mouse macrophage cell line. It is evident from our findings that As-NPs have more potential than As (III) to be used as an antileishmanial agent.
Generalized Gradient Approximation Made Simple.

Generalized gradient approximations (GGA’s) for the exchange-correlation energy improve upon the local spin density (LSD) description of atoms, molecules, and solids. We present a simple derivation of a simple GGA, in which all parameters (other than those in LSD) are fundamental constants. Only general features of the detailed construction underlying the Perdew-Wang 1991 (PW91) GGA are invoked. Improvements over PW91 include an accurate description of the linear response of the uniform electron gas, correct behavior under uniform scaling, and a smoother potential. [S0031-9007(96)01479-2] PACS numbers: 71.15. Mb, 71.45. Gm Kohn-Sham density functional theory [1,2] is widely used for self-consistent-field electronic structure calculations of the ground-state properties of atoms, molecules, and solids. In this theory, only the exchange-correlation energy EXC › EX 1 EC as a functional of the electron spin densities n"srd and n#srd must be approximated. The most popular functionals have a form appropriate for slowly varying densities: the local spin density (LSD) approximation Z d 3 rn e unif
Elliptic Curve Cryptography (ECC) for Host Identity Protocol (HIP)

We compare computational resources required for handling control plane of the Host Identity Protocol (HIP) using Rivest-Shamir-Adleman (RSA) versus Elliptic Curve Cryptography (ECC) encryption algorithms with keys of equivalent strength. We show that servers would establish almost three times more HIP connections per second when ECC is used for generating the session key. For devices with low computational power such as Nokia N810 Internet Tablet, the use of ECC would notably reduce the delay to establish a HIP association. Unless compatibility with legacy RSA/DSA-only systems is needed, the Host Identity may be an ECC key as well, but such a modification would bring only 50 percent additional performance with the current default keys. However the situation becomes different under higher security requirements when employing ECC for the host identification boosts the performance more than four times, and we consider ECC Host Identities desirable in that case.
Cross-Modality Semantic Integration With Hypothesis Rescoring for Robust Interpretation of Multimodal User Interactions

We develop a framework pertaining to automatic semantic interpretation of multimodal user interactions using speech and pen gestures. The two input modalities abstract the user's intended message differently into input events, e.g., key terms/phrases in speech or different types of gestures in the pen modality. The proposed framework begins by generating partial interpretations for each input event as a ranked list of hypothesized semantics. We devise a cross-modality semantic integration procedure to align the pair of hypothesis lists between every speech input event and every pen input event in a multimodal expression. This is achieved by the Viterbi alignment algorithm that enforces the temporal ordering of the input events as well as the semantic compatibility of aligned events. The alignment enables generation of a unimodal, verbalized paraphrase that is semantically equivalent to the original multimodal expression. Our experiments are based on a multimodal corpus in the domain of city navigation. Application of the cross-modality integration procedure to near-perfect (manual) transcripts of the speech and pen modalities show that correct unimodal paraphrases are generated for over 97% of the training and test sets. However, if we replace with automatic speech and pen recognition transcripts, the performance drops to 53.7% and 54.8% for the training and test sets, respectively. In order to address this issue, we devised the hypothesis rescoring procedure that evaluates all candidates of cross-modality integration derived from multiple recognition hypotheses from each modality. The rescoring function incorporates the integration score, N-best purity of recognized spoken locative expressions, as well as distances between coordinates of recognized pen gestures and their interpreted icons on the map. Application of cross-modality hypothesis rescoring improved the performance to 67.5% and 69.9% for the training and test sets, respectively.
Genome-wide association identifies ATOH7 as a major gene determining human optic disc size

Optic nerve assessment is important for many blinding diseases, with cup-to-disc ratio (CDR) assessments commonly used in both diagnosis and progression monitoring of glaucoma patients. Optic disc, cup, rim area and CDR measurements all show substantial variation between human populations and high heritability estimates within populations. To identify loci underlying these quantitative traits, we performed a genome-wide association study in two Australian twin cohorts and identified rs3858145, P = 6.2 × 10−10, near the ATOH7 gene as associated with the mean disc area. ATOH7 is known from studies in model organisms to play a key role in retinal ganglion cell formation. The association with rs3858145 was replicated in a cohort of UK twins, with a meta-analysis of the combined data yielding P = 3.4 × 10−10. Imputation further increased the evidence for association for several SNPs in and around ATOH7 (P = 1.3 × 10−10 to 4.3 × 10−11, top SNP rs1900004). The meta-analysis also provided suggestive evidence for association for the cup area at rs690037, P = 1.5 × 10−7, in the gene RFTN1. Direct sequencing of ATOH7 in 12 patients with optic nerve hypoplasia, one of the leading causes of blindness in children, revealed two novel non-synonymous mutations (Arg65Gly, Ala47Thr) which were not found in 90 unrelated controls (combined Fisher's exact P = 0.0136). Furthermore, the Arg65Gly variant was found to have very low frequency (0.00066) in an additional set of 672 controls.
Relationship Between Childhood Trauma, Mindfulness, and Dissociation in Subjects With and Without Hallucination Proneness

The purpose of this study was to examine the relationship between childhood traumas, mindfulness, and dissociation (more specifically, absorption and depersonalization) in healthy subjects with and without hallucination proneness. A sample of 318 subjects was given the Launay-Slade Hallucination Scale–Revised (R. P. Bentall & P. Slade, 1985). From this sample, 2 groups were formed: one with high and the other with low hallucination proneness. Furthermore, all participants were given the Tellegen Absorption Scale (A. Tellegen & G. Atkinson, 1974), the Cambridge Depersonalization Scale (M. Sierra & G. E. Berrios, 2000), the Southampton Mindfulness Questionnaire (P. D. J. Chadwick et al., 2008), and the Trauma Questionnaire (J. R. E. Davidson, D. Hughes, & D. G. Blazer, 1990). The results showed that in the group with high hallucination proneness, there were significantly more subjects with traumatic experiences than in the group with low predisposition, although no significant difference in the mean number of traumatic experiences undergone in childhood was found between the 2 groups, although there was a trend toward significance. A correlation analysis showed a significant negative association between mindfulness on the one hand and absorption and depersonalization on the other. A positive relationship was also found between childhood traumas and absorption and depersonalization. Finally, multiple mediation analysis showed that the absorption and depersonalization variables acted as mediators between childhood traumas and hallucination proneness. We discuss the importance of the relationship between the variables studied and hallucination proneness and suggest some approaches for their treatment.
Modeling and executing the data warehouse refreshment process

Data warehouse refreshment is often viewed as a problem of maintaining materialized views over operational sources. In this paper, we show that the data warehouse refreshment process is a complex process comprising several tasks, e.g., monitoring, extracting, transforming, integrating and cleaning operational data, deriving new data, building histories and loading the data warehouse. We propose a novel approach for defining and executing the refreshment process based on specifications stored in an object-oriented metadata repository. Our approach considers the multidimensional character of OLAP data and can be used in conjunction with various operational sources and target data warehouses.
Streamflow droughts and probability of their occurrence in a small agricultural catchment

Streamflow droughts and probability of their occurrence in a small agricultural catchment The goal of this work consists in quantitative analysis of the occurrence of droughts and their occurrence probability estimated for a small agricultural catchment on the basis of a multi-annual series of daily streamflows in the Zagożdżonka river at the Płachty Stare gauging station, in the context of observed changes in the stream regime during the multi-annual period 1963-2010. The Zagożdżonka river catchment is one of a few in Poland, with long-term records on rainfall and runoff. To identify streamflow droughts in daily discharge hydrograms, truncation level Q90% (discharge determined from the flow duration curve) was used. Minimum duration of drought amounting to 10 days, was the additional criterion for identification of droughts. The Nizowka2003 model was used for finding distributions of the probability of deficit volume and duration of maximum summer droughts for the Zagożdżonka river. The droughts in the small agricultural catchment under study concern only summer half-years and most often they are of short duration - up to 20 days. Longer droughts, lasting lightly over 2 months, can be expected - once per 10 years. The occurrence of a summer drought lasting almost all the season in the Zagożdżonka river is probable once per 100 years. A weak correlation between the minimum drought discharge and their duration was found. Niżówki i prawdopodobieństwo ich występowania w małej zlewni rolniczej Celem pracy jest ilościowa analiza występowania zjawiska niżówki i prawdopodobieństwa jej występowania w małej zlewni rolniczej, na podstawie długoletniej serii obserwacji przepływów dobowych rzeki Zagożdżonki w profilu Płachty Stare, w kontekście śledzenia zmian w reżimie rzeki w wieloleciu 1963-2010. Zlewnia rzeki Zagożdżonki jest jedną z kilku w Polsce, która posiada długi ciąg pomiarów wartości opadów i odpływu. Na potrzeby wyznaczenia niżówek na hydrogramach dobowych przepływów użyto poziomu odcięcia Q90% (przepływ odczytany krzywej czasów trwania przepływów). Dodatkowym kryterium w wyodrębnieniu niżówek zastosowano minimalny czas trwania zjawiska wynoszący 10 dni. Do wyznaczenia rozkładów prawdopodobieństwa objętości deficytu i czasu trwania niżówek maksymalnych letnich dla rzeki Zagożdżonki użyto programu Nizowka2003. Niżówki w rozpatrywanej małej rolniczej zlewni dotyczą jedynie półrocza letniego i najczęściej trwają krótko - do 20 dni. Raz na 10 lat można spodziewać się niżówek dłuższych, trwających niewiele ponad 2 miesiące. Raz na 100 lat jest prawdopodobne wystąpienie w rzece Zagożdżonce niżówki letniej trwającej prawie przez cały sezon. Pomiędzy minimalnym przepływem niżówek a ich czasem trwania uzyskano słabą zależność.
Abstracting control

The last few years have seen a renewed interest in continuations for expressing advanced control structures in programming languages, and new models such as Abstract Continuations have been proposed to capture these dimensions. This article investigates an alternative formulation, exploiting the latent expressive power of the standard continuation-passing style (CPS) instead of introducing yet other new concepts. We build on a single foundation: abstracting control as a hierarchy of continuations, each one modeling a specific language feature as acting on nested evaluation contexts. We show how iterating the continuation-passing conversion allows us to specify a wide range of control behavior. For example, two conversions yield an abstraction of Prolog-style backtracking. A number of other constructs can likewise be expressed in this framework; each is defined independently of the others, but all are arranged in a hierarchy making any interactions between them explicit. This approach preserves all the traditional results about CPS, e.g., its evaluation order independence. Accordingly, our semantics is directly implementable in a call-by-value language such as Scheme or ML. Furthermore, because the control operators denote simple, typable lambda-terms in CPS, they themselves can be statically typed. Contrary to intuition, the iterated CPS transformation does not yield huge results: except where explicitly needed, all continuations beyond the first one disappear due to the extensionality principle (&eegr;-reduction). Besides presenting a new motivation for control operators, this paper also describes an improved conversion into applicative-order CPS. The conversion operates in one pass by performing all administrative reductions at translation time; interestingly, it can be expressed very concisely using the new control operators. The paper also presents some examples of nondeterministic programming in direct style.
Reading New India: Post-Millennial Indian Fiction in English

Introduction: From Postcolonial India to New India 1.1 'Indianness' since Independence 1.2 Literary 'Indianness' 1.3 New India, a New Canon 2. Urban Scapes 2.1 Mumbai 2.2 Bangalore 3. Chick Lit - Crick Lit 3.1 Chick Lit 3.2 Crick Lit 4. Young India 4.1 Call Centres and Corporate Lives 4.2 MSMs 5. Crime Writing 5.1 Female Detectives 5.2 Difference and Death 6. Fantasy and Epic Myth 6.1 New [Fantastical] India 6.2 Bharat Fantasy 7. Graphic Novels 7.1 The Harappa Files (2011) 7.2 Kashmir Pending (2007) Conclusion: New/Old Stories in Old/New Ways Further Reading Index
GENERALIZATION WITH SUPPORT VECTOR MACHINES IN REINFORCEMENT LEARNING

The conventional reinforcement learning assumes discrete state space. Therefore, it is necessary to make states discrete manually in order to handle continuous state environments. However, if the simple discretization is applied, the number of states increases exponentially with the dimension of the state space, and the learning time increase. In this paper, we propose a state generalization that is able to quickly adapt to environments by using Support Vector Machines. To evaluate this method, we do an experiment on the simulation task that navigates a robot to a goal.
Using the Past to Predict the Future?

Reconstructions of climatic conditions on Earth during the Last Glacial Maximum may help to constrain the likely magnitude of global warming. Predictions of future climate change are subject to considerable uncertainty, for two main reasons: Future factors that may influence climate—such as emissions of greenhouse gases, volcanic eruptions, and changing solar activity—are uncertain; and knowledge of how strongly the climate system responds to external influences, particularly increases in greenhouse gases, is incomplete. One way to summarize this latter type of uncertainty is by estimating the equilibrium climate sensitivity (ECS), which is defined as the equilibrium response of global surface temperature to a doubling of the atmospheric CO2 concentration. On page 1385 of this issue, Schmittner et al. (1) report that the use of spatially more complete paleoclimate data for the Last Glacial Maximum (LGM) shows promise for narrowing the ECS uncertainty ranges relative to previous estimates.
System level interconnect design for network-on-chip using interconnect IPs

As technology scales down, the interconnect for on-chip global communication becomes the delay bottleneck. In order to provide well-controlled global wire delay and efficient global communication, a Network-on-Chip (NoC) architecture was proposed by different authors [1][5][6]. NoC uses Interconnect Intellectual Property (IIP) to connect different resources. In a bottom up approach, this paper first studies the NoC system parameters constrained by the interconnections. Predictions on scaled system parameters such as clock frequency, resource size, global communication bandwidth and inter-resource delay are made for future technologies. Based on these parameters, a global wire planning scheme is proposed. At last, the main IIP modules are described and one possible transmission scheme is demonstrated and simulated.
Unveiling Employee Job Satisfaction: Harnessing Deep Learning for Sentiment Analysis

After the COVID outbreak, the trend in job satisfaction changed drastically and many individuals lost their employment. Understanding the social movement requires careful consideration of the variables affecting job sentiment. This study is primarily interested in examining the sentiments of workers at well-known Information Technology organizations. In the beginning, 1,56,428 reviews from various timelines were scraped from Glassdoor. The remarks are then carefully inspected to realize a variety of elements, and the required preprocessing techniques have been used to facilitate a deeper comprehension. Later, various Deep Learning architectures are given the preprocessed comments. The Bidirectional Gated Recurrent Unit (Bi-GRU) has outperformed all other architectures in terms of many performance measures, even though some other architectures have performed noticeably admirably. The generated result shows a 97% accuracy rate and correctly distinguishes the two classes included in the dataset. Apart from this architecture, nine other architectures are also investigated. Among them, Bi-CuDNNLSTM, GRU, and CNN also performed quite well and produced 97%, 96%, and 90% accuracy respectively.