Miracle-dz/UniFAR-FTUs huggingface dataset:
Theorem Proving with Structured Theories

Motivated by the problem of query answering over multiple structured commonsense theories, we exploit graph-based techniques to improve the efficiency of theorem proving for structured theories. Theories are organized into subtheories that are minimally connected by the literals they share. We presentmessage-passing algorithms that reason over these theories using consequence finding, specializing our algorithms for the case of first-order resolution, and for batch and concurrent theorem proving. We provide an algorithm that restricts the interaction between subtheories by exploiting the polarity of literals. We attempt to minimize the reasoning within each individual partition by exploiting existing algorithms for focused incremental and general consequence finding. Finally, we propose an algorithm that compiles each subtheory into one in a reduced sublanguage. We have proven the soundness and completeness of all of these algorithms.
Supervised clustering: algorithms and applications

This work centers on a novel data mining technique we term supervised clustering. Unlike traditional clustering, supervised clustering assumes that the examples are classified. The goal of supervised clustering is to identify class-uniform clusters that have high probability densities. Three representative-based algorithms for supervised clustering are introduced: a greedy algorithm with random restart, named SRIDHCR, that seeks for solutions by inserting and removing single objects from the current set of cluster representatives, SPAM (a variation of the popular clustering algorithm PAM), and an evolutionary computing algorithm named SCEC. The three algorithms were evaluated using a benchmark consisting of UCI machine learning datasets. As part of the evaluation of the supervised clustering algorithms, we study the landscape for the fitness function that supervised clustering tries to minimize. Results show that the fitness landscape seems to have a "Canyonland" shape with large number of hills and plateaus that seems unforgivable for greedy search strategies. This dissertation also discusses and presents experimental evidence on how local and regional learning techniques could benefit from supervised clustering. Specifically, we introduce a technique for class decomposition and demonstrate with experimental results how it could enhance the performance of simple classifiers. Furthermore, we present a dataset editing technique, we call supervised clustering editing (SCE), which replaces examples of a learned cluster by the cluster representative. Our experimental results demonstrate how dataset editing techniques in general and SCE technique in particular enhance the performance of NN classifiers. Other potential applications of supervised clustering such as summary generation, discovery of interesting regions in spatial databases, and distance function learning are discussed as well.
Antecedent Hindbrain Glucoprivation Does Not Impair the Counterregulatory Response to Hypoglycemia

Recurrent hypoglycemia impairs hormonal counterregulatory responses (CRRs) to further bouts of hypoglycemia. The hypothalamus and hindbrain are both critical for sensing hypoglycemia and triggering CRRs. Hypothalamic glucose sensing sites are implicated in the pathogenesis of defective CRRs; however, the contribution of hindbrain glucose sensing has not been elucidated. Using a rat model, we compared the effect of antecedent glucoprivation targeting hindbrain or hypothalamic glucose sensing sites with the effect of antecedent recurrent hypoglycemia on CRR to hypoglycemia induced 24 h later. Recurrent hypoglycemia decreased sympathoadrenal (1,470 ± 325 vs. 3,811 ± 540 pg/ml in controls [t = 60 min], P = 0.001) and glucagon secretion (222 ± 43 vs. 494 ± 56 pg/ml in controls [t = 60]), P = 0.003) in response to hypoglycemia. Antecedent 5-thio-glucose (5TG) injected into the hindbrain did not impair sympathoadrenal (3,806 ± 344 pg/ml [t = 60]) or glucagon (513 ± 56 pg/ml [t = 60]) responses to subsequent hypoglycemia. However, antecedent 5TG delivered into the third ventricle was sufficient to blunt CRRs to hypoglycemia. These results show that hindbrain glucose sensing is not involved in the development of defective CRRs. However, neural substrates surrounding the third ventricle are particularly sensitive to glucoprivic stimulation and may contribute importantly to the development of defective CRRs.
Managing Drug Use in Danish Club Settings: A Normalized Enterprise?

The article analyzes Danish clubbers’ strategies for taking drugs in night clubs. This exploration is framed within the discussion of a possible normalization of youth drug use. Thus, the article investigates how young drug-users experience the level of acceptability of drug use in clubs and how this perceived acceptability—or rather lack of acceptability—affects their practices around drug-taking. The analysis points towards two distinct strategies which the clubbers make use of when taking drugs in clubs: an assimilative strategy and an opportunistic strategy, and it is shown how these strategies are indicative of the level of acceptability of drugs in club settings. Through this focus on the micro-level, the article adds to the limited amount of literature on this dimension of the normalization thesis. Empirically, the article is based on a Danish mixed methods club study.
siRNA-mediated silencing of integrin β3 expression inhibits the metastatic potential of B16 melanoma cells

Integrins comprise a large family of αβ heterodimeric cell-surface receptors that mediate diverse processes involved in cell-cell and cell-matrix interactions such as cellular adhesion and migration, cell survival and differentiation. It is now well documented that integrins play a crucial role in cancer metastasis and angiogenesis. The β3 integrins appear to have an important stimulatory role in tumour progression and metastasis and, thus, have been often proposed as potential targets for cancer diagnosis and therapy. In this study, we evaluated the in vitro and in vivo properties of B16 mouse melanoma cells with low expression of integrin β3. Proliferation rate, adhesive properties and the ability to migrate and metastasize were studied. Over 90% inhibition of integrin β3 expression was achieved as a result of the transfection with siRNA. No changes in the proliferation rate were observed in siRNA-transfected B16 cells; however, they showed impaired ability to bind to fibronectin. Moreover, inhibition of integrin β3 expression caused almost complete impairment of the ability of B16 cells to migrate through matrigel and metastasize. The mean number of lung metastatic colonies in mice inoculated intravenously with B16 expressing low levels of integrin β3 was decreased to 14 colonies compared to 101 in the control group. These results provide evidence for a direct role of integrin β3 in the adhesion, migration and metastasis processes of mouse melanoma cells and point to the potential therapeutic advantages of siRNAs.
Achievement Results for Second and Third Graders Using the Standards-Based Curriculum Everyday Mathematics

Students using Everyday Mathematics (EM), developed to incorporate ideas from the NCTM Standards, were at normative U.S. levels on multidigit addition and subtraction symbolic computation on traditional, reform-based, and EM-specific test items. Heterogeneous EM 2nd graders scored higher than middleto upper-middle-class U.S. traditional students on 2 number sense items, matched them on others, and were equivalent to a middle-class Japanese group. On a computation test, the EM 2nd graders outperformed the U.S. traditional students on 3 items involving 3-digit numbers and were outperformed on the 6 most difficult test items by the Japanese children. EM 3rd graders outscored traditional U.S. students on place value and numeration, reasoning, geometry, data, and number-story items.
A new approach for video text detection

Text detection is fundamental to video information retrieval and indexing. Existing methods cannot handle well those texts with different contrast or embedded in a complex background. To handle these difficulties, this paper proposes an efficient text detection approach, which is based on invariant features, such as edge strength, edge density, and horizontal distribution. First, it applies edge detection and uses a low threshold to filter out definitely non-text edges. Then, a local threshold is selected to both keep low-contrast text and simplify complex background of high-contrast text. Next, two text-area enhancement operators are proposed to highlight those areas with either high edge strength or high edge density. Finally, coarse-to-fine detection locates text regions efficiently. Experimental results show that this approach is robust for contrast, font-size, font-color, language, and background complexity.
Defining and Measuring Data-Driven Quality Dimension of Staleness

With the growing complexity of data acquisition and processing methods, there is an increasing demand in understanding which data is outdated and how to have it as fresh as possible. Staleness is one of the key, time-related, data quality characteristics, that represents a degree of synchronization between data originators and information systems possessing the data. However, nowadays there is no common and pervasive notion of data staleness, as well as methods for its measurement in a wide scope of applications. Our work provides a definition of a data-driven notion of staleness for information systems with frequently updatable data. For such a data, we demonstrate an efficient exponential smoothing method of staleness measurement, compared to naive approaches, using the same limited amount of memory, based on averaging of frequency of updates. We present experimental results of staleness measurement algorithms that we run on history of updates of articles from Wikipedia.
Massively parallel solutions for molecular sequence analysis

In this paper we present new approaches to high performance protein database scanning on two novel massively parallel architectures to gain supercomputer power at low cost. The first architecture is built around a Beowulf PC-cluster linked by a high-speed network and fine-grained parallel Systola 1024 processor boards connected to each node. The second architecture is the Fuzion 150, a new parallel computer with a linear SIMD array of 1536 processing elements on a single chip. We present the design of a database scanning application based on the Smith-Waterman algorithm in order to derive efficient mappings onto these architectures. The implementations lead to significant runtime savings for large-scale database scanning. This result shows that both architectures provide high-throughput sequence similarity analysis solutions at a good price/performance ratio.
A 1 cycle-per-byte XML parsing accelerator

Extensible Markup Language (XML) is playing an increasing important role in web services and database systems. However, the task of XML parsing is often the bottleneck, and as a result, the target of acceleration using custom hardware or multicore CPUs. In this paper, we detail the design of the first complete field programmable gate array (FPGA) accelerator capable of XML well-formed checking, schema validation, and tree construction at a throughput of 1 cycle per byte (CPB). This is a significant advancement from 40 CPB, the best previous reported commercial result. We demonstrate our design on a Xilinx Virtex-5 board, which successfully saturates a 1 Gbps Ethernet link.
Weighted $p$ -Bits for FPGA Implementation of Probabilistic Circuits

Probabilistic spin logic is a recently proposed computing paradigm based on unstable stochastic units called probabilistic bits (<inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-bits) that can be correlated to form probabilistic circuits (p-circuits). These p-circuits can be used to solve the problems of optimization, inference, and implement precise Boolean functions in an “inverted” mode, where a given Boolean circuit can operate in reverse to find the input combinations that are consistent with a given output. In this brief, we present a scalable field-programmable gate array implementation of such invertible p-circuits. We implement a “weighted” <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-bit that combines stochastic units with localized memory structures. We also present a generalized tile of weighted <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-bits to which a large class of problems beyond invertible Boolean logic can be mapped and how invertibility can be applied to interesting problems such as the NP-complete subset sum problem by solving a small instance of this problem in hardware.
Multi-Label Classification of Patient Notes a Case Study on ICD Code Assignment

In the context of the Electronic Health Record, automated diagnosis coding of patient notes is a useful task, but a challenging one due to the large number of codes and the length of patient notes. We investigate four models for assigning multiple ICD codes to discharge summaries taken from both MIMIC II and III. We present Hierarchical Attention-GRU (HA-GRU), a hierarchical approach to tag a document by identifying the sentences relevant for each label. HA-GRU achieves state-of-the art results. Furthermore, the learned sentence-level attention layer highlights the model decision process, allows easier error analysis, and suggests future directions for improvement.
Methyl 3,5-bis(cyclohexylmethoxy)benzoate

In the title compound, C22H32O4, the atoms of the methyl ester group and the alkoxy O atoms are all coplanar with the central aromatic ring, with an r.m.s. deviation of 0.008 Å. Bonds to the methylene and cyclohexyl groups are also very close to this plane, so that the molecule is essentially flat, apart from the cyclohexyl groups. The mean planes through the cyclohexyl groups are tilted by 30.08 (9) and 36.14 (7)° with respect to the central aromatic ring. In the crystal, pairs of molecules linked by C—H⋯O hydrogen bonds form planar units which are stacked along the a axis, with an average interplanar distance of 3.549 (2) Å. Stacking appears to be stabilized by further weak C—H⋯O hydrogen bonds.
Robust model-free formation control with prescribed performance for nonlinear multi-agent systems

In this paper, we consider the formation control problem for multi-agent systems with unknown nonlinearities and disturbances, under an undirected communication protocol. Exploiting the recently developed prescribed performance control methodology, a robust distributed control scheme of minimal complexity is proposed that achieves and maintains arbitrarily fast and accurately the desired formation. No information regarding the agents' dynamic model is employed in the design procedure. Moreover, contrary to the related works on multi-agent systems, the transient and steady state response is fully decoupled by the underlying graph topology, the control gains selection and the agents' model uncertainties. In particular, the achieved performance is a priori and explicitly imposed by certain designer-specified performance functions. Finally, the theoretical findings are clarified and verified by an extensive simulation study.
A silicon neural probe fabricated using DRIE on bonded thin silicon

A silicon neural probe fabricated using a deep reactive ion etching based process on 250 μm thin silicon wafers was developed. The fabricated probes replicate the design of soft parylene-C based probes embedded in dissolvable needles and can therefore also be used to test the encapsulation properties of parylene-C in-vivo without introducing additional effects introduced by the dissolvable gel. The process also demonstrates the possibility of performing conventional photolithography on substrates bonded to a handle wafer using a backgrinding liquid wax (BGL7080) as an adhesive. This technique would allow integration of Si wafer thinning into the fabrication of neural probes, potentially allowing a range of neural probes of different thicknesses to be fabricated. Fabricated probes were characterized using electrochemical impedance spectroscopy (EIS) yielding a measured impedance value of ~80 kΩ at 1 kHz for 15 μm by 115 μm platinum electrodes, indicating that extracellular neural recordings are possible. The neural probes were inserted into the substantia nigra of a mouse that showed successful recording of neural activity. Probes fabricated using this technique can thus be potentially used in the study of Parkinson's disease.
Finite-time stabilization for discrete fuzzy jump nonlinear systems with time delays

This paper is concerned with the problem of finite-time H∞ control for a class of discrete-time Markovian jump nonlinear systems with time delays represented by Takagi-Sugeno (T-S) model. First, by using fuzzy stochastic Lyapunov-Krasovskii functional approach, sufficient conditions are derived such that the resulting close-loop system is stochastic finite-time bounded and satisfies a prescribed H∞ disturbance attenuation level in a given finite-time interval. Second, sufficient criteria on stochastic finite-time H∞ stabilization via fuzzy state feedback are provided, and the fuzzy state feedback controller is designed by solving an optimization problem in terms of linear matrix inequalities. Finally, a numerical example is given to show the validity of the proposed designed techniques.
Effect of auditory, tactile, visual, and vestibular intervention on length of stay, alertness, and feeding progression in preterm infants

This study determined whether an auditory, tactile, visual, and vestibular intervention (ATVV) reduced the length of hospitalization of 37 preterm infants by increasing the proportion of alert behavioral states, thereby improving their feeding progression. Participants comprised 12 infants born between 23 and 26 weeks’gestation with normal head ultrasounds and 25 CNS‐injured infants born between 23 and 31 weeks’gestation. Infants were randomly assigned to the control group (11 males, five females) or study group (seven males, 14 females) at 32 weeks’postconceptional age. ATVV intervention was administered to the study group for 15 minutes, twice daily, 5 days per week, from 33 weeks of age until discharge. The study group demonstrated increased alertness during the first 5 minutes of intervention, which was significantly correlated to length of stay (p<0.05). The proportion of nippled (teat) intake increased significantly faster for the study group (p=0.0001). Infants in the study group were discharged at a mean of 36.54 weeks, 1.6 weeks earlier than control infants (p<0.05). ATVV intervention facilitated increased alertness, faster transition to complete nipple feeding, and decreased length of hospitalization.
Instruction scheduling for VLIW processors under variation scenario

Process variations in components like adders, multipliers, etc., of different Integer Functional Units (IFUs) in VLIW (Very Long InstructionWord) processors may cause these units to operate at various speeds, resulting in non-uniform latency IFUs. Worst-case techniques to deal with the non-uniform latency IFUs may incur significant performance and/or leakage energy loss. In this work, we propose two process variation-aware compiletime techniques to handle non-uniform latency IFUs. In the first technique, namely ‘turn-off’, we turn off all the process variation affected high latency IFUs. In the second technique, namely ‘on-demand turn-on’, we use some of the process variation affected high latency IFUs by turning them on whenever there is a requirement. Our experimental results show that with these techniques, the non-uniform latency IFU can be tackled without much performance penalty. The proposed techniques also achieve significant reduction in leakage energy consumption because of turning off of some of the IFUs.
Insights into Neonatal Oral Feeding through the Salivary Transcriptome

Background. The development of safe and effective oral feeding skills in the newborn is complex and may be associated with significant morbidities. Our understanding of neonatal oral feeding maturation at the molecular level is limited, providing an opportunity to utilize emerging molecular techniques to accurately assess neonatal oral feeding skills. Objective. To identify key regulatory genes in neonatal saliva involved in successful oral feeding. Methods. Previously, our laboratory identified 9,286 genes in saliva that statistically significantly altered their gene expression as premature newborns gained advanced oral feeding skills. In this report, genes previously identified underwent an updated and targeted pathway analysis with Ingenuity Pathway Analysis (IPA) to identify potential candidate genes involved in successful oral feeding. Genes were considered if they were in the five most significantly up- and down-regulated physiological pathways and were associated with the keywords “feeding”, “digestion” and “development”. Results. There were 2,186 genes that met criteria. Pathways associated with feeding behavior, cranial nerve development, and the development of the nervous, skeletal, and muscular systems were highlighted. Discussion. These data provide important insights into the biological processes involved in oral feeding in the newborn at a molecular level and identify novel pathways associated with successful oral feeding.
Village Phone Program, Commodification Of Mobile Phone Set And Empowerment Of Women

The objective of the article is to examine the role of the Village Phone (VP) Program of the Grameen Bank in the empowerment of women. The article takes a case study approach that draws on a close examination of the literatures on the VP Program in Bangladesh, its role in providing telephone service to rural people, creating income opportunities for the rural women (who predominantly operate the owner-operated village pay-phone program) and thereby empowering them. We find that the VP empowered village women economically and socially by reducing and/or eliminating their dependence on other members of their families and giving them increased roles in family decision making. The empowering role of the VP also spilled over to its users. T he article demonstrates how an innovative idea by social entrepreneurs in the Information and Communication Technology ( ICT) sector can act as change agent in transforming the lot of rural poor women by empowering them and making them self reliant.
Reasons for quitting among emerging adults and adolescents in substance-use-disorder treatment.

OBJECTIVE Understanding developmental differences in reasons for quitting substance use may assist clinicians in tailoring treatments to different clinical populations. This study investigates whether alcohol-disordered and problem-drinking emerging adults (i.e., ages 18-25 years) have different reasons for quitting than younger adolescents (i.e., ages 13-17 years). METHOD Using a large clinical sample of emerging adults and adolescents, we compared endorsement rates for 26 separate reasons for quitting between emerging adults and adolescents who were matched on clinical severity. Then age group was regressed on total, interpersonal, and personal reasons for quitting, and mediation tests were conducted with variables proposed to be developmentally salient to emerging adults. RESULTS Among both age groups, self-control reasons were the most highly endorsed. Emerging adults had significantly fewer interpersonal reasons for quitting (Cohen's d = 0.20), and this association was partially mediated by days of being in trouble with one's family. There were no differences in personal reasons or total number of reasons for quitting. CONCLUSIONS Our findings are consistent with developmental theory suggesting that emerging adults experience less social control, which here leads to less interpersonal motivation to refrain from alcohol and drug use. As emerging adults in clinical samples may indicate few interpersonal reasons for quitting, one challenge to tailoring treatments for them will be identifying innovative ways of leveraging social supports and altering existing social networks.