Miracle-dz/UniFAR-FTUs huggingface dataset:
Peat in the mountains of New Guinea

Peatlands are common in montane areas above 1,000 m in New Guinea and become extensive above 3,000 m in the subalpine zone. In the montane mires, swamp forests and grass or sedge fens predominate on swampy valley bottoms. These mires may be 4–8 m in depth and up to 30,000 years in age. In Papua New Guinea (PNG) there is about 2,250 km2 of montane peatland, and Papua Province (the Indonesian western half of the island) probably contains much more. Above 3,000 m, peat soils form under blanket bog on slopes as well as on valley floors. Vegetation types include cushion bog, grass bog and sedge fen. Typical peat depths are 0.5‒1 m on slopes, but valley floors and hollows contain up to 10 m of peat. The estimated total extent of mountain peatland is 14,800 km2 with 5,965 km2 in PNG and about 8,800 km2 in Papua Province. The stratigraphy, age structure and vegetation histories of 45 peatland or organic limnic sites above 750 m have been investigated since 1965. These record major vegetation shifts at 28,000, 17,000‒14,000 and 9,000 years ago and a variable history of human disturbance from 14,000 years ago with extensive clearance by the midHolocene at some sites. While montane peatlands were important agricultural centres in the Holocene, the introduction of new dryland crops has resulted in the abandonment of some peatlands in the last few centuries. Despite several decades of research, detailed knowledge of the mountain peatlands is poor and this is an obstacle to scientific management.
Coupling an Annotated Corpus and a Morphosyntactic Lexicon for State-of-the-Art POS Tagging with Less Human Effort

This paper investigates how to best couple hand-annotated data with information extracted from an external lexical resource to improve POS tagging performance. Focusing on French tagging, we introduce a maximum entropy conditional sequence tagging system that is enriched with information extracted from a morphological resource. This system gives a 97.7% accuracy on the French Treebank, an error reduction of 23% (28% on unknown words) over the same tagger without lexical information. We also conduct experiments on datasets and lexicons of varying sizes in order to assess the best trade-off between annotating data vs. developing a lexicon. We find that the use of a lexicon improves the quality of the tagger at any stage of development of either resource, and that for fixed performance levels the availability of the full lexicon consistently reduces t he need for supervised data by at least one half.
Structural Characteristics and Non-Linear Optical Behaviour of a 2-Hydroxynicotinate-Containing Zinc-Based Metal-Organic Framework

Materials with non-linear optical (NLO) properties play an important role in the construction of electronic devices for optical communications, optical data processing and data storage. With this aim in mind, a Zn(II)-based metal-organic framework {[Zn2(nica)2(bpy)1.5(H2O)]·0.5(bpy)·3H2O}n (1), was synthesized using 4,4ʹ-bipyridine (bpy) and a potentially bidentate ligand, 2-hydroxynicotinic acid (H2nica) with a salicylate binding moiety. A single-crystal X-ray diffraction analysis revealed that compound 1 crystallized in the orthorhombic space group Fdd2 and was composed of a three dimensional porous framework. Since Fdd2 belonged to a class of non-centrosymmetric space groups, we therefore investigated the non-linear optical behaviour of compound 1. Photoluminescence studies revealed that compound 1 exhibited a blue light emission with a maxima at 457 nm.
Modelling Traffic Flow with Constant Speed using the Galerkin Finite Element Method

At macroscopic level, traffic can he described as a continuum flow. Lighthill Witham anti Richards (LWR) have developed a traffic flow model based on the fluid dynamics continuity equation, which is known as the first order LWR traffic flow model The resulting first order partial differential equation (PDE) can be analytically solved for some special cases, given initial and boundary conditions, and numerically using for example the finite element method (FEM). This paper makes use of the Galerkin FEM to solve the LWR model with constant speed. The road is divided into it number of road segments (elements) using the Galerkin FEM. Each element consists of two nodes. Each mule hits one degree (if freedom (d o f), namely the traffic density. The FEM provides a solution for the degrees of freedom, i.e. traffic densities of each node. The resulting simultaneous equations arc solved at different tinge steps using the Euler backward tinge-integration algorithm. In Belgium and also in the Netherlands, there is a special technique that can be used in order to prevent traffic jams anti increasing safety in situations with high volume of cars on the roads, i.e. block driving. It is a technique where cars drive in groups by order of the police when the roads are crowded. In this paper block driving is used as a practical example of the LWR model with constant speed. Thereby, it is simulated using the Galerkin FEM and the results tire compared with the analytical solution. The FIRM gives good results providing that: the road segments and time steps are small enough. A road with length 5000 m, constant speed of 25 m/s, segment length of 100 m anti time steps of 1 s gives good results for the studied case. At points of traffic density rate discontinuities, depending on the road segment size and time step size, the Galerkin FEM is accurate anti requires reasonable computational effort. From the research work carried out in this paper, it is found that the Galerkin FEM is suitable for modelling traffic flow at macroscopic level. The element size and tinge step size tire important parameters in determining the convergence of the solution in case of discontinuities in traffic density rate. Although this paper considers the case of constant speed, the technique can be extended in the future to include the case of non-constant speed, i.e. speed as a function of traffic density.
Direct Computation of Nonlinear Soft-Tissue Deformation

Abstract A method for computing nonlinear soft–tissuedeformation caused by simulated surgical pro-cedures is presented. A mass–spring system isused to model patient individual soft–tissue.Instead of simulating dynamic behaviour, theintroduced approach directly estimates therest position of the system. Very fast and ro-bust nonlinear soft–tissue deformation is com-puted using an optimization approach.The multi–layer soft–tissue model consid-ers features like skin turgor and gravity. Themodel takes into account the nonlinear stress–strain relationship of soft–tissue and the factthat soft–tissue is almost incompressible dueto its liquid components.The approach to soft–tissue deformation ispart of an integrated system for craniofacialsurgical simulation. The system is capable ofsimulating bonecutting andbonerealignmentwith integrated interactive collision detection.Furthermore, soft–tissuedeformationandcut-ting due to the application of surgical instru-ments can be visualized. 1 Introduction
Critical appraisal of the exposure-potential restriction rule.

Schlesselman's rule to restrict all case-control studies to those individuals potentially at risk of exposure was designed to reduce a bias toward the null. Found to be without basis, the need for the rule came into question, and Schlesselman and Stadel now suggest several other arguments on behalf of the rule and extend its jurisdiction from case-control to all epidemiologic studies. It is not necessary to decide on a single view of fairness on the contrast of case-control designs in order to assess the impact on precision of the exposure-potential restriction rule. There exists a class of counter-examples for which the rule reduces precision from either perspective of a fair contrast. This class includes all studies in which the exposure prevalence is closer to its optimal value for precision prior to applying the rule than it is after the rule is applied. Raising the exposure prevalence diminishes precision in such examples, even if the number of cases and the number of controls are held constant between the 2 studies. Concerning fairness in the contrast of study designs, enhancement of precision does not justify a rule to restrict every study to people not known to lack the opportunity for exposure. The other argument in favor of the exposure-potential restriction rule is that adherence to the rule incidentally will result in control of confounding, if the indicator of exposure potential also happens to be a confounder. The fault with this argument is that restriction is an irrevocable way of controlling possible confounding. The mere possibility of inadvertently controlling confounding does not provide a good reason to use every indicator of exposure opportunity as a restriction criteria in every study. This is what the proposed rule requires. Schlesselman and Stadel introduce 3 new arguments to defend the exposure-potential restruction rule. 1 of the 3 arguments draws an analogy between the proposed rule and theuse of randomization in experimental studies. The 2nd argument draws an analogy between potential for exposure and potential for disease. The last argument invokes a requirement for epidemiologic studies to respond to questions of relevance and importance. Regarding the latter argument, they provide only illustrations, among them that "the real issue" in a study of the effects of oral contraceptives (OCs) "is the risk of disease in women who choose this contraceptive method. " The authors identify the experience of individuals who are not OC users as "irrelevant to the purpose of the study. " None of the arguments Schlesselman and Stadel propose answer the question of why every study should be free of individuals who were barred by some nonconfounder from becoming exposed. This is the question if one accepts the experience of unexposed individuals as essential to studying the effects of any exposure, and if one acknowledges the long-standing use of restriction to control confounding.
Establishing the baseline for using plankton as biosensor

Plankton is at the bottom of the food chain. Microscopic phytoplankton account for about 50% of all photosynthesis on Earth, corresponding to 50 billion tons of carbon each year, or about 125 billion tonnes of sugar[1]. Plankton is also the food for most species of fish, and therefore it represents the backbone of the aquatic environment. Thus, monitoring plankton is paramount to infer potential dangerous changes to the ecosystem. In this work we use a collection of plankton species extracted from a large dataset of images from the Woods Hole Oceanographic Institution (WHOI), to establish a basic set of morphological features for supporting the use of plankton as a biosensor. Using a perturbation detection approach, we show that it is possible to detect deviation from the average space of features for each species of plankton microorganisms, that we propose could be related to environmental threat or perturbations. Such an approach can open the way for the development of an automatic Artificial Intelligence (AI) based system for using plankton as biosensor.
Cs 6604: Data Mining

1. A sample space is the set of all possible outcomes of a trial or experiment. For a die roll, the sample space would be the set {1, 2, 3, 4, 5, 6}. 2. A σ-algebra of a set X is a collection of subsets of X, and is closed under the complement and union set operators. For example, a trivial σ-algebra for any set X is the set containing the empty set and X itself. 3. A random variable is a variable that takes on values from a sample space, based on some distribution. These variables can represent a random trial (such as a die toss) and its results. 4. A distribution defines a probability or likelihood that a random variable takes each of the values from a sample space.
GBI-SA: GBI Feature with Subtle Adjustment for Robust Non-rigid 3D Shape Retrieval

Deformable shape retrieval has posed a challenge to researchers, which is becoming more and more important. This paper addresses non-rigid 3D shape retrieval in terms of a subtle adjustment strategy. For this purpose, we first construct a new global shape descriptor based on biharmonic distance, which uses the connectivity between vertices for natural shape representation. Then, in order to enhance retrieval ability, we propose a subtle adjustment method to provide discriminative information. Finally, we depend on experiment to evaluate the performance of the proposed method. Comparison results have proved that the proposed GBI-SA retrieval method is superior to state-of-the-art methods, including SD-GDM, mesh SIFT, MDS-CM-BOF, Shape DNA, and WESD.
The Impact of a Telephone-Based Chronic Disease Management Program on Medical Expenditures

Abstract The impact of a payer-provided telephone-based chronic disease management program on medical expenditures was evaluated using claims data from 126,245 members in employer self-ensured health plans (16,224 with a chronic disease in a group enrolled in the self-management program, 13,509 with a chronic disease in a group not participating in the program). A random effects regression model controlling for retrospective risk, age, sex, and diagnosis with a chronic disease was used to determine the impact of program participation on market-adjusted health care expenditures. Further confirmation of results was obtained by an ordinary least squares model comparing market- and risk-adjusted costs to the length of participation in the program. Participation in the program is associated with an average annual savings of $1157.91 per enrolled member in health care expenditures. Savings increase with the length of participation in the program. The results support the use of telephone-based patient self-management of chronic disease as a cost-effective means to reduce health care expenditures in the working-age population. (Population Health Management 2016;19:156–162)
Gene expression of zinc-alpha 2-glycoprotein in normal human epidermal and buccal epithelia.

Zinc-alpha 2-glycoprotein (Zn alpha 2gp) is almost ubiquitous in body fluids. We have found it to be also present in stratified epithelia. We compare its mRNA expression in cells from human epidermis and buccal mucosa cultured in media of graded differentiation potential (attained by varying calcium ion concentration and adding serum). The Zn alpha 2gp gene is upregulated in both epithelia with differentiation and further with exposure to interferon gamma or transforming growth factor beta 1. The upregulation by these agents increases with differentiation in epidermal cells, but peaks in the low-differentiation medium in buccal epithelia. We compared gene expression levels of Zn alpha 2gp with those of characteristic cytokeratins of stratified epithelia (k5 for basal cells, K10 for epidermal suprabasal cells, and K13 for mucosal suprabasal cells). This pattern correlation associates Zn alpha 2gp cell-type dependently with late differentiation, i.e. with keratin K10 in epidermis and with K13 in buccal epithelium.
Late language emergence at 24 months: an epidemiological study of prevalence, predictors, and covariates.

PURPOSE The primary objectives of this study were to determine the prevalence of late language emergence (LLE) and to investigate the predictive status of maternal, family, and child variables. METHOD This is a prospective cohort study of 1,766 epidemiologically ascertained 24-month-old singleton children. The framework was an ecological model of child development encompassing a wide range of maternal, family, and child variables. Data were obtained using a postal questionnaire. Item analyses of the 6-item Communication scale of the Ages and Stages Questionnaire (ASQ; D. Bricker & J. Squires, 1999; J. Squires & D. Bricker, 1993; J. Squires, D. Bricker, & L. Potter, 1997; J. Squires, L. Potter, & D. Bricker, 1999) yielded a composite score encompassing comprehension as well as production items. One SD below the mean yielded good separation of affected from unaffected children. Analyses of bivariate relationships with maternal, family, and child variables were carried out, followed by multivariate logistic regression to predict LLE group membership. RESULTS 13.4% of the sample showed LLE via the ASQ criterion, with 19.1% using the single item of "combining words. " Risk for LLE at 24 months was not associated with particular strata of parental educational levels, socioeconomic resources, parental mental health, parenting practices, or family functioning. Significant predictors included familial history of LLE, male gender, and early neurobiological growth. Covariates included psychosocial indicators. CONCLUSION Results are congruent with models of language emergence and impairment that posit a strong role for neurobiological and genetic mechanisms of onset that operate across a wide variation in maternal and family characteristics.
Cystathionine beta synthase deficiency promotes oxidative stress, fibrosis, and steatosis in mice liver.

BACKGROUND & AIMS Cystathionine beta-synthase (CBS) deficiency causes severe hyperhomocysteinemia, which confers diverse clinical manifestations, notably liver disease. To investigate this aspect of hyperhomocysteinemia, we performed a thorough investigation of liver pathology in CBS-deficient mice, a murine model of severe hyperhomocysteinemia. METHODS The degree of liver injury and inflammation was assessed by histologic examination, by measurements of products of lipid peroxidation, and by formation of carbonyl groups on protein as a measure for the occurrence of protein oxidation. Analysis of profibrogenic, proinflammatory factors and cell apoptosis was performed by Western blots, real-time quantitative reverse-transcription polymerase chain reaction, caspase-3 activity, DNA laddering, and TUNEL assay. RESULTS Histologic evaluation of liver specimens of 8- to 32-week-old CBS-deficient mice showed that CBS-deficient mice develop inflammation, fibrosis, and hepatic steatosis, concomitant with an enhanced expression of tissue inhibitor of metalloproteinase-1, alpha-smooth muscle actin, pro(alpha)1 collagen type I, transforming growth factor-beta1, and proinflammatory cytokines. Moreover, even if the proapoptotic protein Bax was dominantly expressed and Bcl-2 was down-regulated, caspase-3 was not activated, DNA laddering was not detected, and number of positive TUNEL cells was not increased in liver of CBS-deficient mice compared with wild-type mice. CONCLUSIONS The results show that hyperhomocysteinemia in liver of CBS-deficient mice promotes oxidative stress, which may cause mitochondrial damage in association with activation of hepatic stellate cells, leading to liver injury. The absence of caspase-3 activation, DNA fragmentation, and TUNEL-positive cells shows that protective signals may counteract apoptotic signals in liver of CBS-deficient mice.
COPING WITH CONFLICT: DEFENSIVE STRATEGIES AND CHRONIC WARFARE IN THE PREHISPANIC NAZCA REGION

Warfare was a prevalent phenomenon throughout the Andes during the Late Intermediate period (LIP; AD 1000–1450). A salient research topic within broader investigations of conflict is how populations cope with chronic warfare. This article utilizes statistical and GIS-based analyses of architectural features and settlement patterns to reconstruct defensive coping mechanisms among groups living in 15 fortified settlements in the Nazca region of Peru. This research evaluates how populations deployed artificial defenses (fortifications), natural defensibility, and settlement placement to best protect themselves and critical resources from enemy incursions. Intersite variation in fortification was primarily driven by population size: the smallest and most vulnerable settlements were the most heavily fortified and occupied the least accessible areas. Variation in fortification investment within each site was driven by differences in the accessibility of approaches leading to the residential sector of a site. Settlement patterns were largely driven by natural defensibility, large viewsheds, and proximity to economic resources. This research demonstrates that LIP populations made optimal trade-offs between competing defensive variables, revealing highly patterned regional defensive strategies. Broader spatial, settlement, and architectural data indicate that warfare in the region was chronic and internecine. En los Andes, la guerra fue una ocurrencia frecuente y significativa durante el período Intermedio tardío (1000-1450 dC). La adaptación de las poblaciones a la guerra continua es un tema importante dentro de las investigaciones generales sobre conflictos. Este artículo utiliza análisis estadísticos y por medio de SIG de rasgos arquitectónicos y patrones de asentamiento para reconstruir los mecanismos defensivos de 15 asentamientos fortificados en la región de Nazca, Perú. Específicamente, esta investigación evalúa cómo se emplearon las defensas artificiales (fortificaciones), la defensibilidad natural y la localización de los asentamientos para proteger a las poblaciones y los recursos críticos durante las incursiones enemigas. Los resultados demuestran que la pendiente del terreno fue el factor más significativo que guió la construcción de las fortificaciones dentro de los sitios. Las variaciones en el tipo de fortificaciones entre los distintos sitios fueron impulsadas principalmente por el tamaño de la población, por lo que los asentamientos más pequeños y más vulnerables son fuertemente fortificados y ocupan las áreas menos accesibles. Los patrones de asentamiento fueron impulsados por la defensibilidad natural, la amplitud de las líneas de vista y la proximidad a los recursos económicos. Esta investigación demuestra que las poblaciones del Intermedio tardío tuvieron que equilibrar variables defensivas contrapuestas, revelando estrategias defensivas regionales con patrones similares. Más en general, los datos sobre asentamiento y arquitectura indican que la guerra en la región fue recurrente e intensa.
“A Feeling of Connectedness”: Perspectives on a Gentle Yoga Intervention for Women with Major Depression

Major depressive disorder (MDD) is one of the most common and debilitating health conditions in women in the United States and worldwide. Many women with MDD seek out complementary therapies for their depressive symptoms, either as an adjunct or alternative to the usual care. The purpose of this study is to understand the experiences of women who participated in a yoga intervention for their depression. The findings from this interpretive phenomenological study are derived from interviews with and daily logs by 12 women with MDD who took part in an 8-week gentle yoga intervention as part of a larger parent randomized, controlled trial. Results show that the women's experience of depression involved stress, ruminations, and isolation. In addition, their experiences of yoga were that it served as a self-care technique for the stress and ruminative aspects of depression and that it served as a relational technique, facilitating connectedness and shared experiences in a safe environment. Future long-term research is warranted to evaluate these concepts as potential mechanisms for the effects of yoga for depression.
Model-free reinforcement learning as mixture learning

We cast model-free reinforcement learning as the problem of maximizing the likelihood of a probabilistic mixture model via sampling, addressing both the infinite and finite horizon cases. We describe a Stochastic Approximation EM algorithm for likelihood maximization that, in the tabular case, is equivalent to a non-bootstrapping optimistic policy iteration algorithm like Sarsa(1) that can be applied both in MDPs and POMDPs. On the theoretical side, by relating the proposed stochastic EM algorithm to the family of optimistic policy iteration algorithms, we provide new tools that permit the design and analysis of algorithms in that family. On the practical side, preliminary experiments on a POMDP problem demonstrated encouraging results.