Miracle-dz/UniFAR-FTUs huggingface dataset:
LSO/LYSO Crystals for Calorimeters in Future HEP Experiments

Because of their high stopping power (X0=1.14 cm), fast (τ = 40 ns) bright (4 times BGO) scintillation with small temperature coefficient (-0.2%/°C) and superb radiation hardness, LSO/LYSO crystals are chosen to construct electromagnetic calorimeters (ECAL) of total absorption nature. One critical issue for this application is the light response uniformity (LRU) of long crystal bars with tapered geometry, which is affected by the non-uniform light yield along the crystal, the self-absorption and the optical focusing effect. Following a ray-tracing simulation study, an uniformization method was developed by roughening one side surface with LRU of better than 3% achieved. LSO/LYSO crystals are also proposed as the active material for a sampling ECAL for future HEP experiments in severe radiation environment. Preliminary designs with Pb or W absorber are described. Measurements of light collection efficiency (LCE) for prototype Shashlik cells with wavelength shifting fiber readout are presented. Future development on LSO/LYSO crystal based sampling ECAL is discussed.
What Do Unions Do to Executive Compensation

In this paper we estimate the relation between union presence within a firm and CEO compensation, using a unique panel of publicly listed companies for the period 1992 to 2001. We find that, on average, union presence: 1) is significantly associated with lower levels of total CEO compensation; 2) affects the mix of CEO compensation by providing higher levels of base pay but much lower stock option values; 3) lowers dispersion across the major components of CEO remuneration and 4) does not significantly reduce the performance sensitivity of CEO compensation as compared to non-union firms. These results are consistent with several models of union influence.
Stem Cells as a Cure For Amyotrophic Lateral Sclerosis

29 Introduction Amyotrophic Lateral Sclerosis (ALS), commonly known as “Lou Gehrig’s Disease,” is a fatal neurodegenerative disorder characterized by the slow degeneration of the motor neurons (MNs) of the entire human body, including, but not limited to, the MNs of the cerebral cortex, spinal cord and limb, axial and respiratory muscles. ALS is an adult-onset, rapidly progressive disease, killing 50% of patients within 2 and a half years of symptom onset. There are two types of disease onset, Limb-onset, which is characterized by degeneration of upper and lower motor neurons (UMN and LMN) identified by weakness, fasciculations and spasticity of the limbs, and Bulbar-onset, degeneration of tongue muscles causing weakness and fasciculations in the tongue as well as spastic dysarthria and dysphagia. Eventually, no matter the type of onset, the motor neuron degeneration spreads throughout the body resulting in paralysis of the limbs and eventually the diaphragm, causing respiratory distress and ultimately death (Kiernan, et al. 2011). ALS has been categorized into two classes, familial ALS, which is genetic and presented through a Mendelian pattern of inheritance, accounts for 5-10% of people with ALS, and Sporadic ALS which accounts for the remaining 90% (Kiernan, et al. 2011). At present, the etiology remains complex and unresolved and has confounded scientists over the century. As a result, finding a treatment for ALS has proved to be extremely challenging. The etiology seems to be multifaceted with many genetic and molecular factors contributing directly and indirectly to the degeneration of motor neurons, including gene mutations, neurotoxins, glutamateinduced excitotoxicity, and structural abnormalities of the mitochondrion, sodium potassium pump and axonal structures. Mutations in SOD1 gene generates a toxic gain of function of SOD1 enzyme, formation of free radicals and formation of aggregates due to improper folding of the SOD1 protein, resulting in impaired motor neuron function and neuron death (Kiernan, et al. 2011). The SOD1 gene, which accounts for 20% of familial ALS, is of significant importance because it can transduce mice into effective ALS models for stem cell therapy and other research (Gurney, et al. 1994). To date, only one drug, Riluzole, remains effective in treating ALS symptoms, by inhibiting glutamate receptors and slowing the disease progression by 3-6 months. This unfortunate lack of a significant cure or treatment may be a result of the inadequacy of diagnostic tests. By the time a patient is diagnosed with ALS, many of their motor neurons have allready died, and their muscles atrophied. Since ALS can only be diagnosed once clinical symptoms appear, there is no early detection and therefor, no early prevention (Kiernan, et al. 2011). Stem cells, however, provide an astonishing and Abstract
Designing for context-aware health self-monitoring, feedback, and engagement

There is a novel opportunity to increase awareness of health activities in a person's daily life. One way to do that is through context-aware self-monitoring. We explore design insights from field work and field testing different methods for self-monitoring. We present an innovative design for establishing context-aware self-monitoring that has the potential to improve health.
Self-folding and self-actuating robots: A pneumatic approach

Self-assembling robots can be transported and deployed inexpensively and autonomously in remote and dangerous environments. In this paper, we introduce a novel self-assembling method with a planar pneumatic system. Inflation of pouches translate into shape changes, turning a sheet of composite material into a complex robotic structure. This new method enables a flat origami-based robotic structure to self-fold to desired angles with pressure control. It allows a static joint to become dynamic, self-actuate to reconfigure itself after initial folding. Finally, the folded robot can unfold itself at the end of a robotic application. We believe this new pneumatic approach provides an important toolkit to build more powerful and capable self-assembling robots.
Using Web Page Titles to Rediscover Lost Web Pages

Titles are denoted by the TITLE element within a web page. We queried the title against the the Yahoo search engine to determine the page's status (found, not found). We conducted several tests based on elements of the title. These tests were used to discern whether we could predict a pages status based on the title. Our results increase our ability to determine bad titles but not our ability to determine good titles.
Management of Adolescent Depression in the Primary Care Setting: An Educational Program for Providers

Background: The prevalence of adolescent depression is estimated at 15-20% in the general population and often undertreated. The primary care provider is in a prime position to identify and treat depression in this age group. However, many providers feel uncomfortable with treating and managing depression in adolescents, due to a lack of education or experience. Purpose: The focus of this quality improvement project was to educate primary care providers on the current recommendations for the management of adolescent depression and provide an education sheet for both the medical and non-medical treatment of adolescent depression. An educational intervention was presented to providers at a physician-owned private practice family clinic in Massachusetts. Pre-test and post-test scores were compared to determine the change in knowledge and confidence levels. Results: Eight providers attended the education presentation and completed the pre-test and seven of these providers also completed the post-test. The results indicated an improvement in provider’s level of confidence of understanding ways to manage adolescent depression (p=.030) and in being familiar with evidenced based management options (p=.045). There was no change in the provider’s confidence in ability to manage adolescent depression or discuss a variety of treatment options or in the provider’s understanding of the CBT model following the education intervention. Discussion: Due to limited education regarding mental health issues in primary care programs, offering supplemental education may help to meet this need as specialized providers are limited. The findings suggest that a longer term education intervention may be useful in increasing knowledge and confidence level of providers related to the management of adolescent depression in the primary care setting.
The essential role of pair matching in cluster-randomized experiments, with application to the Mexican Universal Health Insurance Evaluation

A basic feature of many field experiments is that investigators are only able to randomize clusters of individuals — such as households, communities, firms, medical practices, schools, or classrooms — even when the individual is the unit of interest. To recoup some of the resulting eciency loss, many studies pair similar clusters and randomize treatment within pairs. Other studies (including almost all published political science field experiments) avoid pairing, in part because some prominent methodological articles claim to have identified serious problems with this “matched-pair cluster-randomized” design. We prove that all such claims about problems with this design are unfounded. We then show that the estimator for matched-pair designs favored in the literature is appropriate only in situations where matching is not needed. To address this problem without modeling assumptions, we generalize Neyman’s (1923) approach and propose a simple new estimator with much improved statistical properties. We also introduce methods to cope with individual-level noncompliance, which most existing approaches incorrectly assume away. We show that from the perspective of, among other things, bias, eciency, or power, pairing should be used in cluster-randomized experiments whenever feasible; failing to do so is equivalent to discarding a considerable fraction of one’s data. We develop these techniques in the context of a randomized evaluation we are conducting of the Mexican Universal Health Insurance Program.
Calcified iliopsoas abscess caused by Enterococcus faecalis.

A 67-year-old woman was referred to our department for the treatment of cryoglobulinemic vasculitis associated with primary Sjögren’s syndrome. One month after the initiation of immunosuppressive therapy, hemorrhagic rectal ulcers were observed and rectal resection was performed. Although a computed tomography (CT) scan obtained on admission was unremarkable (Picture 1), CT repeated two months after the initiation of immunosuppressive therapy revealed a calcified and gas-forming abscess in the right iliopsoas (Picture 2, arrow). Enterococcus faecalis was detected using a CT-guided biopsy. The empirical administration of biapenem (0.6 g/day) and clindamycin (1.2 g/day) for nine days was not effective; however, the patient was successfully treated using incisional drainage and the sequential administration of antibiotics [imipenem (1 g/day) and minocycline (200 mg/day) for three weeks, followed by ampicillin (6 g/day) for two weeks and amoxicillin (1.5 g/day) for one month] selected based on antibiotic susceptibility testing. Iliopsoas abscesses are classified as primary or secondary, depending on the presence or absence of underlying pathologies, such as gastrointestinal or genitourinary disease (1). Staphylococcus aureus and Mycobacterium tuberculosis are well-known causative organisms; however, infection with E. faecalis is rare, even in patients with gastrointestinal lesions (1, 2). For example, Enterococcus was detected in only one out of 99 (1%) CT-guided drainage procedures for deep intramuscular and musculoskeletal abscesses (2). However, this case demonstrates that E. faecalis can form calcified iliopsoas abscesses resembling those caused by M. tuberculosis.
A genetic variant in proximity to the gene LYPLAL1 is associated with lower hunger feelings and increased weight loss following Roux-en-Y gastric bypass surgery

Abstract Objective: Bariatric surgery is the most efficient treatment of severe obesity. We investigated to what extent BMI- or waist-hip ratio (WHR)-related genetic variants are associated with excess BMI loss (EBMIL) two years after Roux-en-Y gastric bypass (RYGB) surgery, and elucidated the affected biological pathways. Methods: Two-hundred fifty-one obese patients (age: 43 ± 10.7, preoperative BMI: 45.1 ± 6.1 kg/m2, 186 women) underwent RYGB surgery and were followed up after two years with regard to BMI. Patients were genotyped for 32 single-nucleotide polymorphisms (SNPs) that were investigated with regard to their impact on response to RYGB and preoperatively measured Three Factor Eating Questionnaire (TFEQ) scores. Results: Homozygous T carriers of the SNP rs4846567 in proximity to the Lysophospholipase-like 1 (LYPLAL1) gene showed a 7% higher EBMIL compared to wild-type and heterozygous carriers (p = 0.031). TT-allele carriers showed furthermore lower scores for Hunger (74%, p < 0.001), lower Disinhibition (53%, p < 0.001), and higher Cognitive restraint (21%, p = 0.017) than GG/GT carriers in the TFEQ. Patients within the lowest quartile of Hunger scores had a 32% greater EBMIL compared to patients in the highest quartile (p < 0.001). Conclusion: The LYPLAL1 genotype is associated with differences in eating behavior and loss of extensive body weight following RYGB surgery. Genotyping and the use of eating behavior-related questionnaires may help to estimate the RYGB-associated therapy success.
Toward a Case-Based Framework for Imitation Learning in Robotic Agents

Imitation learning is a skill essential to human development and cognition [6, 5]. Naturally, imitation learning has become a topic of focus for robotics research as well, particularly in interactive robots [1, 2]. In imitating the actions of a teacher, a cognitive agent learns the demonstrated action such that it may perform a similar action later and achieve a similar goal. Thus, we expect that a cognitive robot that learns from imitation would reuse what it has learned from one experience to reason about addressing related, but di↵erent, problem scenarios. The eventual goal of this work is to use a case-based approach to enable imitation learning in interactions such as the following. A human teacher guides the robot to complete a task, such as scooping the contents of one container into another. The robot records the demonstrated actions and observed objects, saving the demonstration as a source case in its case memory. At a later time, the robot is asked to repeat the scooping task, but in a new, target environment containing a di↵erent set of object features to parameterize and execute the task. Next, the robot would transfer its representation of the scooping task to accommodate for the di↵erences between the source and target environments, and then execute an action based on the transferred representation to achieve the goal state in the target environment. Using a case-based framework to address this problem allows us to represent demonstrations as individual experiences in the robot’s case memory, and provides us with a framework for identifying, transferring, and executing a relevant source case demonstration in an unfamiliar target environment. The main research questions we plan to address are as follows:
3-Hitting set on bounded degree hypergraphs: Upper and lower bounds on the kernel size

We study upper and lower bounds on the kernel size for the 3-HITTING SET problem on hypergraphs of degree at most 3, denoted 3- 3-hs.We first show that, unless P=NP, 3-3-hs on 3-uniform hypergraphs does not have a kernel of size at most 35k/19 > 1.8421k. We then give a 4k - k0.2692 kernel for 3-3-hs that is computable in time O(k1.2692). This result improves the upper bound of 4k on the kernel size for 3- 3-hs, given by Wahlstrom. We also show that the upper bound results on the kernel size for 3-3-hs can be generalized to the 3-HS problem on hypergraphs of bounded degree Δ, for any integer-constant Δ > 3.
Microwave and Millimeter-Wave Radiometric and Radiosonde Observations in an Arctic Environment

Abstract In a recent paper by Mattioli et al., a significant difference was observed between upper-tropospheric and lower-stratospheric water vapor profiles as observed by two radiosonde systems operating in the Arctic. The first was the Vaisala RS90 system as operated by the U.S. Department of Energy’s Atmospheric Radiation Measurement Program; the second was the operational radiosondes launched by the U.S. National Weather Service that used the Sippican VIZ-B2 type. Observations of precipitable water vapor by ground-based microwave radiometers and GPS did not reveal these differences. However, both the microwave radiometer profiler (MWRP) and the ground-based scanning radiometer (GSR) contain channels that receive a significant response from the upper-tropospheric region. In this paper, it is shown that brightness temperature (Tb) observations from these instruments are in consistent agreement with calculations based on the RS90 data but differ by several degrees with calculations based on the VIZ radio.
VIBE 2.0: Visual Integration for Bayesian Evaluation

Summary: Data fusion methods are powerful tools for evaluating experiments designed to discover measurable features of directly unobservable systems. We describe an interactive software platform, Visual Integration for Bayesian Evaluation, that ingests or creates Bayesian posterior probability matrices, performs data fusion and allows the user to interactively evaluate the classification power of fusing various combinations of data sources, such as transcriptomic, proteomics, metabolomics, biochemistry and function. Availability: http://omics.pnl.gov/software/VIBE.php Contact: bj@pnl.gov Supplementary information: Supplementary data are available at Bioinformatics online.
One-Hour-Ahead Load Forecasting Using Neural Networks

Load forecasting has always been the essential part of an efficient power system planning and operation. Several electric power companies are now forecasting load power based on conventional methods. However, since the relationship between load power and factors influencing load power is nonlinear, it is difficult to identify its nonlinearity by using conventional methods. Most of papers deal with 24-hour-ahead load forecasting or next day peak load forecasting. These methods forecast the demand power by using forecasted temperature as forecast information. But, when the temperature curves changes rapidly on the forecast day, load power changes greatly and forecast error would going to increase. In conventional methods neural networks uses all similar day's data to learn the trend of similarity. However, learning of all similar day's data is very complex, and it does not suit learning of neural network. Therefore, it is necessary to reduce the neural network structure and learning time. To overcome these problems, we propose a one-hour-ahead load forecasting method using the correction of similar day data. In the proposed prediction method, the forecasted load power is obtained by adding a correction to the selected similar day data.
Object recognition and categorization using modal matching

Recently the authors (1993) have proposed a new method for establishing correspondences and computing canonical descriptions, based on the idea of describing objects by their generalized symmetries, as defined by the object's vibration of deformation modes. In this paper they extend this method to the problems of object recognition and categorization. Examples of recognizing hand tools and airplanes are shown. <<ETX>>
Inhibition of Melanogenesis by Gallic Acid: Possible Involvement of the PI3K/Akt, MEK/ERK and Wnt/β-Catenin Signaling Pathways in B16F10 Cells

Gallic acid is one of the major flavonoids found in plants. It acts as an antioxidant, and seems to have anti-inflammatory, anti-viral, and anti-cancer properties. In this study, we investigated the effects of gallic acid on melanogenesis, including the activation of melanogenesis signaling pathways. Gallic acid significantly inhibited both melanin synthesis and tyrosinase activity in a dose- and time-dependent manner, and decreased the expression of melanogenesis-related proteins, such as microphthalmia-associated transcription factor (MITF), tyrosinase, tyrosinase-related protein-1 (TRP1), and dopachrome tautomerase (Dct). In addition, gallic acid also acts by phosphorylating and activating melanogenesis inhibitory proteins such as Akt and mitogen-activated protein kinase (MEK)/extracellular signal-regulated kinase (ERK). Using inhibitors against PI3K/Akt (LY294002) or MEK/ERK-specific (PD98059), the hypopigmentation effect was suppressed, and the gallic acid-initiated activation of MEK/ERK and PI3K/Akt was also revoked. Gallic acid also increased GSK3β and p-β-catenin expression but down-regulated p-GSK3β. Moreover, GSK3β-specific inhibitor (SB216763) restored gallic acid-induced melanin reduction. These results suggest that activation of the MEK/ERK, PI3K/Akt, and inhibition of Wnt/β-catenin signaling pathways is involved in the melanogenesis signaling cascade, and that activation by gallic acid reduces melanin synthesis via down-regulation of MITF and its downstream signaling pathway. In conclusion, gallic acid may be a potentially agent for the treatment of certain skin conditions.
On density effects and large structure in turbulent mixing layers

Plane turbulent mixing between two streams of different gases (especially nitrogen and helium) was studied in a novel apparatus. Spark shadow pictures showed that, for all ratios of densities in the two streams, the mixing layer is dominated by large coherent structures. High-speed movies showed that these convect at nearly constant speed, and increase their size and spacing discontinuously by amalgamation with neighbouring ones. The pictures and measurements of density fluctuations suggest that turbulent mixing and entrainment is a process of entanglement on the scale of the large structures; some statistical properties of the latter are used to obtain an estimate of entrainment rates. Large changes of the density ratio across the mixing layer were found to have a relatively small effect on the spreading angle; it is concluded that the strong effects, which are observed when one stream is supersonic, are due to compressibility effects, not density effects, as has been generally supposed.
Sparse Models of Natural Language Text

In statistical text analysis, many learning problems can be formulated as a minimization of a sum of a loss function and a regularization function for a vector of parameters (feature coefficients). The loss function drives the model to learn generalizable patterns from the training data, whereas the regularizer plays two important roles: to prevent the models from capturing idiosyncrasies of the training data (overfitting) and to encode prior knowledge about the model parameters. When learning from high-dimensional data such as text, it has been empirically observed that relatively few dimensions are relevant to the predictive task (Forman, 2003). How can we capitalize on this insight and choose which dimensions are relevant in an informed and principled manner? Sparse regularizers provide a way to select relevant dimensions by means of regularization. However, past work rarely encodes non-trivial prior knowledge that yields sparse solutions through a regularization function. This thesis investigates the applications of sparse models—especially structured sparse models—as a medium to encode linguistically-motivated prior knowledge in textual models to advance NLP systems. We explore applications of sparse NLP models in temporal models of text, word embeddings, and text categorization. Sparse models come with their own challenges, since new instantiations of sparse models often require a specialized optimization method. This thesis also presents optimization methods for the proposed instantiations of sparse models. Therefore, the goals of this thesis are twofold: (i) to show how sparsity can be used to encode linguistic information in statistical text models, and (ii) to develop efficient learning algorithms to solve the resulting optimization problems.