Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling and Optimization of a Concentrating PV-Mirror System

The paper presents results on a novel low concentra tion system for photovoltaic/ hybrid module [2], its geo metric modelling and the optimal working parameters. The l ow concentration system is build up of a PV module and two mirrors, one on the left side and symmetrically on the right side along the length of the PV module. Our objective is to maximize the received direct radiat ion of the PV or hybrid module, maintaining an overall geometric size of the system as small as possible w ith a minimum number of the tracking steps. Two cases wer e considered: the first case when the reflected solar radiation from each mirror sweeps the whole surface of the PV module increasing by almost 2x the amount of radiation that sweeps the PV-surface; the second ca se when the reflected light from each mirror partially sweeps the PV-module surface, building together one cover of light on the plane and increasing the amou nt f radiation that falls on the module surface around 1 x. The simulations were developed considering the equatorial tracking system for the geographical loc ati n of the Brasov Romania area, using specific region al parameters, considering the ideal meteorological conditions. Through numerical simulations the parameters that influence functionality of the asse mbly can be identified, making optimization possible. The main geometric parameters of the model are: the inclination angle between the PV-module and the mir ror (θ), the ratio L1/ L2 ( ε) , the incidence angle [4], υM – maximum incidence angle (when positioned to the rig ht, υM > 0), υmminimum incidence angle (when positioned to the left, υm =υM), υM11, υM12, υM13 – incidence angle reflected by the right mirror, M1 on the PV module, right extreme, median and left extreme and analogue υM21, υM22, υM23 for the left mirror, M2. For the angle υM we considered the values υM= 15°, 7.5, 3.75°, 1,875°, knowing that the sun moves with ~15°/hour. During the first case, ε1 depends on the θ angle as well as on the maximum incidence angle υM and it increases due to the θ and υM values; in the second case, ε2 depends only on the values of θ and not on υM. The overall size in the first case (described by the ratio ε1) tends to overlap the overall size of the second case system ( ε2) when the tracking accuracy increases; during continuous orientation of the first case system, the overall s izes of the two cases become equal. Table I
Complex layout analysis based on contour classification and morphological operations

In this paper, a technique appropriate for document image layout analysis is presented. The technique is appropriate for colored and complex layouts of newspapers and journals. It is a hybrid technique that makes use of the contour classification method and also applies morphological operators. Detailed experiments on 2000 scanned images from newspapers gave an accuracy of more than 95% while the computational cost per page is less than a half second.
Cue Integration

Scientists examining how people understand other minds have long thought that this task must be something like how people perceive the physical world. This comparison has proven to be deeply generative, as models of physical perception and social cognition have evolved in parallel. In this article, I propose extending this classic analogy in a new direction by proposing cue integration as a common feature of social cognition and physical perception. When encountering complex social cues—which happens often—perceivers use multiple processes for understanding others’ minds. Like physical senses (e.g., vision or audition), social cognitive processes have often been studied as though they operate in relative isolation. In the domain of physical perception, this assumption has broken down, following evidence that perception is instead characterized by pervasive integration of multisensory information. Such integration is, in turn, elegantly described by Bayesian inferential models. By adopting a similar cue integration framework, researchers can similarly understand and formally model the ways that we perceive others’ minds based on complex social information.
Epidemiology of Dysglycemia in Pregnant Oklahoma American Indian Women.

CONTEXT Minority communities are disproportionately affected by diabetes, and minority women are at an increased risk for glucose intolerance (dysglycemia) during pregnancy. OBJECTIVES In pregnant American Indian women, the objectives of the study were to use current criteria to estimate the prevalence of first-trimester (Tr1) dysglycemia and second-trimester (Tr2) incidence of gestational diabetes mellitus (GDM) and to explore new candidate measures and identify associated clinical factors. DESIGN This was a prospective cohort study. In Tr1 we performed a 75-g, 2-hour oral glucose tolerance test (OGTT) and glycated hemoglobin (HbA1c) to determine the following: fasting insulin; homeostasis model assessment of insulin resistance; serum 1,5-anhydroglucitol; noninvasive skin autofluorescence (SCOUT). We defined dysglycemia by American Diabetes Association and Endocrine Society criteria and as HbA1c of 5.7% or greater. In Tr2 in an available subset, we performed a repeat OGTT and SCOUT. PARTICIPANTS Pregnant American Indian women (n = 244 at Tr1; n = 114 at Tr2) participated in the study. OUTCOMES The prevalence of dysglycemia at Tr1 and incidence of GDM at Tr2 were measured. RESULTS At Tr1, one woman had overt diabetes; 36 (15%) had impaired glucose tolerance (American Diabetes Association criteria and/or abnormal HbA1c) and 59 (24%) had GDM-Tr1 (Endocrine Society criteria). Overall, 74 (30%) had some form of dysglycemia. Associated factors were body mass index, hypertension, waist/hip circumferences, SCOUT score, fasting insulin, and homeostasis model assessment of insulin resistance. At Tr2, 114 of the Tr1 cohort underwent a repeat OGTT and SCOUT, and 26 (23%) had GDM. GDM-Tr2 was associated with increased SCOUT scores (P = .029) and Tr1 body mass index, waist/hip circumferences, diastolic blood pressure, fasting insulin, and triglyceride levels. Overall, dysglycemia at Tr1 and/or Tr2 affected 38% of the women. CONCLUSIONS Dysglycemia at some point during pregnancy was common among American Indian women. It was associated with features of insulin resistance and may confer long-term health risks for mother and child.
Leveraging Strength-Based Dynamic Information Flow Analysis to Enhance Data Value Prediction

Value prediction is a technique to increase parallelism by attempting to overcome serialization constraints caused by true data dependences. By predicting the outcome of an instruction before it executes, value prediction allows data dependent instructions to issue and execute speculatively, hence increasing parallelism when the prediction is correct. In case of a misprediction, the execution is redone with the corrected value. If the benefit from increased parallelism outweighs the misprediction recovery penalty, overall performance could be improved. Enhancing performance with value prediction therefore requires highly accurate prediction methods. Most existing general value prediction techniques are local, that is, future outputs of an instruction are predicted based on outputs from previous executions of the same instruction. In this article, we investigate leveraging strength-based dynamic information flow analysis to enhance data value prediction. We use dynamic information flow analysis (DIFA) to determine when a specific value predictor can perform well and even outperform other predictors. We apply information theory to mathematically prove the validity and benefits of correlating value predictors. We also introduce the concept of the linear value predictors, a new technique that predicts a new value from another one using a linear relation. We finally present a variant of stride predictor that we call update stride. We then conduct an empirical analysis using Pin, a dynamic binary instrumentation tool, and DynFlow, a dynamic information flow analysis tool, that we apply to programs from the SPECjvm2008 and Siemens benchmarks. Our empirical measurements support our mathematical theory and allow us to make important observations on the relation between predictability of data values and information flow. Our analysis and empirical results show that the values of a set of selected variables can be predicted with a very high accuracy, up to 100%. Such prediction is based on the previous history and/or the values of one or more other source variables that have strong information flow into the predicted variable. Using our selection criteria, we show that a DIFA-directed predictor outperforms hardware value prediction for all subject programs, and sometimes by a significant margin. This was observed even when using an ideal tagged hardware value prediction table that does not suffer from aliasing or capacity misses.
CD34+ Blood Cells Accelerate Vascularization and Healing of Diabetic Mouse Skin Wounds

Diabetes is characterized by poor circulation and impaired angiogenesis, which appear to contribute to the frequent skin lesions and poor wound healing common in diabetic patients. Therapies to improve circulation commonly improve wound healing in diabetic patients. Administration of circulating CD34+ cells, cells that can function as endothelial cell progenitors, accelerates blood flow restoration to ischemic limbs of diabetic mice. We have investigated the potential of these cells to accelerate revascularization and healing in full-thickness skin wounds of hypoinsulinemic (streptozotocin-treated) diabetic mice. Wounds were injected with human CD34+ or CD34– peripheral blood mononuclear cells or no cells, and analyzed for vascularity and healing at various times thereafter. Treatment with CD34+ enriched cells decreased wound size by 4 days after treatment, accelerated epidermal healing, and rapidly and dramatically accelerated revascularization of the wounds compared to controls. Initially increased vascularization was mediated principally by an increase in vessel diameter, but later, both an increase in vascular size and number were observed. These findings indicate that blood-derived progenitors may have therapeutic potential in the treatment of skin lesions in the setting of diabetes, and give insights into how bone marrow cells exert their effects on neovascularization.
Preloaded hopping with linear multi-modal actuation

For more dexterous and agile legged robot locomotion, alternative actuation has been one of the most long-awaited technologies. The goal of this paper is to investigate the use of newly developed actuator, the so-called Linear Multi-Modal Actuator (LMMA), in the context of legged robot locomotion, and analyze the behavioral performance of it. The LMMA consists of three discrete couplings which enable the system to switch between different mechanical dynamics such as instantaneous switches between series elastic and fully actuated dynamics. To test this actuator for legged locomotion, this paper introduces a one-legged robot platform we developed to implement the actuator, and explains a novel control strategy for hopping, i.e. “preloaded hopping control”. This control strategy takes advantage of the coupling mechanism of the LMMA to preload the series elasticity during the flight phase to improve the energy efficiency of hopping locomotion. This paper shows a series of experimental results that compare the control strategy with a simple sinusoidal actuation strategy to discuss the benefits and challenges of the proposed approach.
The Abject Failure of Keyword IR for Mathematics Search: Berkeley at NTCIR-10 Math

This paper demonstrates that classical content search using individual keywords is inadequate for mathematical formulae search. For the NTCIR10 Math Pilot Task, the authors used a standard indexing by content word for search coupled with search for components of mathematical formulae. This was followed by formula extraction from the top ranked documents. Performance was terrible, even for partial relevance. The further inclusion of some manual reformulation of topics into queries did not improve retrieval performance.
Increasing Autonomy of Learning Sensorimotor Transformations with Dynamic Neural Fields

In this paper, we introduce a neuraldynamic architecture that enables autonomous learning of sensory-motor mappings in a closed behavioral loop. Dynamic neural fields ensure stability of perceptual and motor representations, a neural-dynamic representation of the condition-of-satisfaction autonomously terminates the current action and enables activation of the next action, triggering a transient learning process when appropriate. Sampling of the high-dimensional space of the sensory-motor mapping is facilitated by a representation of the behaviorally salient states through localized activity peaks in the visual and motor neural-dynamic representations. We present the basic concepts of our autonomous learning architecture, a robotic implementation using a dynamic vision sensor mounted on a pan-tilt unit, which enables learning in a closed behavioral loop, and demonstrate functioning of the architecture in a simple learning scenario.
Local Transient Characterization of Thermofluid Heat Transfer Coefficient at Solid-liquid Nano-interfaces

The demands for increasingly smaller, more capable, and higher power density technologies in microelectronics, energy, or aerospace systems have heightened the need for new methods to manage and characterize extreme heat fluxes (EHF). Microscale liquid cooling techniques are viewed as a promising solution for removing heat from high heat flux (HHF) systems. However, there have been challenges in physical understanding and predicting local thermal transport at the interface of micro and nanoscale structures/devices due to ballistic effects and complex coupling of mass, momentum, and energy transport at the solidâ€"liquidâ€"vapor interfaces over multiple time and length scales. Moreover, itâ€TMs challenging to experimentally validate new HHF models due to lack of high resolution techniques and measurements.
Contextual stance classification of opinions: A step towards enthymeme reconstruction in online reviews

Enthymemes, that are arguments with missing premises, are common in natural language text. They pose a challenge for the field of argument mining, which aims to extract arguments from such text. If we can detect whether a premise is missing in an argument, then we can either fill the missing premise from similar/related arguments, or discard such enthymemes altogether and focus on complete arguments. In this paper, we draw a connection between explicit vs. implicit opinion classification in reviews, and detecting arguments from enthymemes. For this purpose, we train a binary classifier to detect explicit vs. implicit opinions using a manually labelled dataset. Experimental results show that the proposed method can discriminate explicit opinions from implicit ones, thereby providing encouraging first step towards enthymeme detection in natural language texts.
Phanerozoic Stromatolites: Noncompetitive Ecologic Restriction by Grazing and Burrowing Animals

The abundance of stromatolites (algal laminated sedimentary structures) in the Precambrian followed by a decline in the Phanerozoic is explained by the evolution and diversification during the Phanerozoic of grazing animals which feed on surface algal mats and of burrowing animals which destroy sedimentary laminations.
Institutional Repository Orthopaedic sport biomechanics : a new paradigm

This article proposes a new paradigm, "Orthopaedic sport biomechanics", for the understanding of the role of biomechanics in preventing and managing sports injury. Biomechanics has three main roles in this paradigm: (1) injury prevention, (2) immediate evaluation of treatment, and (3) long-term outcome evaluation. Related previous studies showing the approach in preventing and managing anterior cruciate ligament rupture and anterior talofibular ligament tear are highlighted. Orthopaedics and biomechanics specialists are encouraged to understand what they could contribute to the current and future practice of sports medicine.
RAPID MULTIPLICATION OF RECTANGULAR MATRICES *

The number of essential multiplications required to multiply matrices of size N N and N N is bounded by CN log N. Key words, matrix multiplication, tensor rank, algebraic complexity Introduction. Let Rank(K, M, N) denote the number of essential multiplications required to multiply a KM matrix by an M N matrix, i.e., the rank of the 3-dimensional tensor defining this matrix multiplication. We show here, by two different routes, the existence of a positive number ce such that Rank (N, N, N) -< CN log N. THEOREM. There is a positive constant a 2 log 2/5 log 5 0.17227 such that Rank ((N, N, N)) O(N2(log N)2). Remark. This agrees well with the trivial lower bound Rank ((N, N, N))->N2. Proof. The proof may be done in two ways. Each relies on existing basic constructions (each due to Sch/Snhage), and minor modifications to existing techniques for combining basic constructions (i.e., the exponential direct sum theorem, partial matrix multiplication and approximate algorithms). The modifications involve (1) selecting a binomial coefficient to maximize an "area" rather than a "volume" (which allows the agreement between upper and lower bounds) and (2) doing two arguments at once (e.g., the exponential direct sum theorem and approximate algorithms) which serves only to improve the "error bound" from N to C(log N)2. Proof version 1 (partial matrix multiplication). Begin with the following construction, due to Sch6nhage [3]: (all + x2a12)(b21 / x2b11)(c11) + (all + x2a13)(b31)(Cll xc21) /(all / x2aE2)(bEl xb12)(c2) + (al + x2a23)(b31 + xb2)(Cl2 + xc21)-(al)(b21 + b31)(Cll + c2) xE(allbc / allb12CEl / alEbElC11 / a13b31Cll / aEEb21c12 / a23b31c12) +x3p(a,b,c,x). This construction performs an approximate evaluation of the partial matrix product (all a12 a13 b21 0 Cll c12 trace 0 a22 a23/ b31 0, C21 C22/ with five multiplications. Notice that five is also the trivial lower bound for this matrix product, obtained by counting independent elements of the matrix A. It is this equality * Received by the editors July 17, 1980, and in final form October 16, 1981. Mathematical Sciences Department, IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598. 467 D ow nl oa de d 05 /0 8/ 14 to 1 71 . 6 7. 21 6. 23 . R ed is tr ib ut io n su bj ec t t o SI A M li ce ns e or c op yr ig ht ; s ee h ttp :// w w w . s ia m . o rg /jo ur na ls /o js a. ph p
Atomic actions -- molecular experience: theory of pervasive gaming

In this article we attempt to describe and analyze the formalisms of pervasive games and pervasive gaming (PG). As the title indicates, PG consists of atomic entities that nevertheless merge into a molecular structure that exhibits emergent features during the actual game-play. The article introduces four axes of PG (mobility, distribution, persistence, and transmediality). Further, it describes and analyses three key units of PG (rules, entities, and mechanics) as well as discusses the role of space in PG by differentiating between tangible space, information-embedded space, and accessibility space. The article is generally concerned with classifying the indispensable components of pervasive games and, in addition, it lists the invariant features of pervasive game-play, meaning the epistemology that is tied to this new kind of gaming situated on the borderline between corporeal and immaterial space. Of particular interest are game rules in pervasive gaming, since they seem to touch upon both the underlying, formal structure of the game (i.e., the ontology of PG) and the actual play vis-à-vis physical and/or virtual constraints (i.e., the PG epistemology).
Competitive analysis of dynamic power management strategies for systems with multiple power saving states

We present strategies for "online" dynamic power management (DPM) based on the notion of the competitive ratio that allows us to compare the effectiveness of algorithms against an optimal strategy. This paper makes two contributions: it provides a theoretical basis for the analysis of DPM strategies for systems with multiple power down states; and provides a competitive algorithm based on probabilistically generated inputs that improves the competitive ratio over deterministic strategies. Experimental results show that our probability-based DPM strategy improves the efficiency of power management over the deterministic DPM strategy by 25%, bringing the strategy to within 23% of the optimal offline DPM.
Exploiting time in electronic health record correlations

OBJECTIVE To demonstrate that a large, heterogeneous clinical database can reveal fine temporal patterns in clinical associations; to illustrate several types of associations; and to ascertain the value of exploiting time. MATERIALS AND METHODS Lagged linear correlation was calculated between seven clinical laboratory values and 30 clinical concepts extracted from resident signout notes from a 22-year, 3-million-patient database of electronic health records. Time points were interpolated, and patients were normalized to reduce inter-patient effects. RESULTS The method revealed several types of associations with detailed temporal patterns. Definitional associations included low blood potassium preceding 'hypokalemia. ' Low potassium preceding the drug spironolactone with high potassium following spironolactone exemplified intentional and physiologic associations, respectively. Counterintuitive results such as the fact that diseases appeared to follow their effects may be due to the workflow of healthcare, in which clinical findings precede the clinician's diagnosis of a disease even though the disease actually preceded the findings. Fully exploiting time by interpolating time points produced less noisy results. DISCUSSION Electronic health records are not direct reflections of the patient state, but rather reflections of the healthcare process and the recording process. With proper techniques and understanding, and with proper incorporation of time, interpretable associations can be derived from a large clinical database. CONCLUSION A large, heterogeneous clinical database can reveal clinical associations, time is an important feature, and care must be taken to interpret the results.
A Study on Neural Network Method for Personal Credit Evaluation

This paper analyses the neural network method for personal credit evaluation. Firstly, it introduces personal credit evaluation and its research. Secondly, it analyses the characteristics of two types of commonly used methods for personal credit evaluation. Then it introduces the structure and characteristics of artificial neural network and puts forward 10 indicators for personal credit evaluation. On this basis, it designs Elman neural network and tries to use this network to evaluate personal credit. According to the results of experimental verification, this personal credit evaluation algorithm shows a high accuracy for the evaluation of personal credit.