Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of ST14A Cells for Studying Modulation of Voltage-Gated Calcium Channels

In medium spiny neurons (MSNs) of the striatum, dopamine D2 receptors (D2Rs) specifically inhibit the Cav1.3 subtype of L-type Ca2+ channels (LTCs). MSNs are heterogeneous in their expression of dopamine receptors making the study of D2R pathways difficult in primary neurons. Here, we employed the ST14A cell line, derived from embryonic striatum and characterized to have properties of MSNs, to study Cav1.3 current and its modulation by neurotransmitters. Round, undifferentiated ST14A cells exhibited little to no endogenous Ca2+ current while differentiated ST14A cells expressed endogenous Ca2+ current. Transfection with LTC subunits produced functional Cav1.3 current from round cells, providing a homogeneous model system compared to native MSNs for studying D2R pathways. However, neither endogenous nor recombinant Cav1.3 current was modulated by the D2R agonist quinpirole. We confirmed D2R expression in ST14A cells and also detected D1Rs, D4Rs, D5Rs, Gq, calcineurin and phospholipase A2 using RT-PCR and/or Western blot analysis. Phospholipase C β-1 (PLCβ-1) expression was not detected by Western blot analysis which may account for the lack of LTC modulation by D2Rs. These findings raise caution about the assumption that the presence of G-protein coupled receptors in cell lines indicates the presence of complete signaling cascades. However, exogenous arachidonic acid inhibited recombinant Cav1.3 current indicating that channels expressed in ST14A cells are capable of modulation since they respond to a known signaling molecule downstream of D2Rs. Thus, ST14A cells provide a MSN-like cell line for studying channel modulation and signaling pathways that do not involve activation of PLCβ-1.
On the Identification of Ozone Recovery

As ozone depleting substances decline, stratospheric ozone is displaying signs of healing in the Antarctic lower stratosphere. Here we focus on higher altitudes and the global stratosphere. Two key processes that can influence ozone recovery are evaluated: dynamical variability and solar proton events (SPEs). A nine‐member ensemble of free‐running simulations indicates that dynamical variability dominates the relatively small ozone recovery signal over 1998–2016 in the subpolar lower stratosphere, particularly near the tropical tropopause. The absence of observed recovery there to date is therefore not unexpected. For the upper stratosphere, high latitudes (50–80°N/S) during autumn and winter show the largest recovery. Large halogen‐induced odd oxygen loss there provides a fingerprint of seasonal sensitivity to chlorine trends. However, we show that SPEs also have a profound effect on ozone trends within this region since 2000. Thus, accounting for SPEs is important for detection of recovery in the upper stratosphere.
Problem Solving Applied to Language Generation

This research was supported at SRI International by the Defense Advanced Research Projects Agency under contract N00039--79--C--0118 with the Naval Electronic Systems Command. The views and conclusions contained in this document are those of the author and should not be interpreted as representative of the official policies either expressed or implied of the Defense Advanced Research Projects Agency, or the U. S. Government. The author is grateful to Barbara Grosz, Gary Hendrix and Terry Winograd for comments on an earlier draft of this paper.
Use of cadmium isotopes to distinguish sources of cadmium in New Zealand agricultural soil: Preliminary results

In New Zealand’s agricultural soils, phosphate fertiliser applications are the main source of cadmium (Cd). In 1997, the NZ fertiliser industry discontinued sourcing rock phosphate from Nauru (about 450 mg Cd/ Kg P) and began producing superphosphate from other rock phosphate sources (such as Morocco), which have generally lower concentrations of Cd. Research on the concentration of Cd in soils from the long-term irrigation trials at the Winchmore research farm (Canterbury) indicates that Cd accumulation rates have started to slow in the period since 1997 (Fig. 1) (McDowell 2012).
Extended Clique percolation method to detect overlapping community structure

Community detection in social network is a prominent issue in the study of network system as it helps to understand the structure of a network. A member of a social network can be part of more than one group or community. As a member can be overlapped between more than one group, overlapping community detection technique need to be considered in order to identify the overlapping nodes. Clique percolation method is a community detection algorithm which is mostly used for detecting overlapping communities. The problem with this method is that it does not cover the complete network. Hence some nodes may not be a part of any community irrespective of their connectivity. In this paper a novel approach has been introduced to extend the clique percolation method so that each and every connected node will be part of at least one community. The main strategy is to find the initial communities using clique percolation method and then expanding those communities by adding left out nodes which are not included in any community. Left out nodes are included to initial communities based on their belonging coefficient. Real world networks are used to evaluate the proposed algorithm. Quality of the detected community structure is measured by modularity measure which shows proposed method detects communities of better quality over Clique percolation method.
Exploration of different types of intonational deviations in foreign-accented and synthesized speech

The study provides an analysis of the basic manifestations of intonational deviations in foreign-accented (American English accent in German) and synthesized speech. It takes into account the crucial influence of the used model of intonation description and makes a major distinction between individual deviations that cause the impression of foreignness or unnaturalness immediately when they occur, and others that do so only when an accumulation of several such deviations does not allow for a meaningful interpretation anymore. It is argued that this is due to the high variability allowed in prosodic contexts. A closer description of the first group of deviations includes the transfer of categories and of the phonetic realizations of categories as well as a discussion of seemingly unmotivated errors and the most likely causes of intonation errors in synthesized speech. Finally, it is shown that in the case of foreign accent the language-specific manifestations of the presented deviations combine to create a characteristic overall impression of foreignness that is recognizable independently of the segmental content of an utterance.
Finding Induced Subgraphs via Minimal Triangulations

Potential maximal cliques and minimal separators are combinatorial objects which were introduced and studied in the realm of minimal triangulation problems including Minimum Fill-in and Treewidth. We discover unexpected applications of these notions to the field of moderate exponential algorithms. In particular, we show that given an n-vertex graph G together with its set of potential maximal cliques, and an integer t, it is possible in time the number of potential maximal cliques times $O(n^{O(t)})$ to find a maximum induced subgraph of treewidth t in G and for a given graph F of treewidth t, to decide if G contains an induced subgraph isomorphic to F. Combined with an improved algorithm enumerating all potential maximal cliques in time $O(1.734601^n)$, this yields that both the problems are solvable in time $1.734601^n$ * $n^{O(t)}$.
The oxidative refolding of hen lysozyme and its catalysis by protein disulfide isomerase

The oxidative refolding of hen lysozyme has been studied by a variety of time‐resolved biophysical methods in conjunction with analysis of folding intermediates using reverse‐phase HPLC. In order to achieve this, refolding conditions were designed to reduce aggregation during the early stages of the folding reaction. A complex ensemble of relatively unstructured intermediates with on average two disulfide bonds is formed rapidly from the fully reduced protein after initiation of folding. Following structural collapse, the majority of molecules slowly form the four‐disulfide‐containing fully native protein via rearrangement of a highly native‐like, kinetically trapped intermediate, des‐[76–94], although a significant population (∼30%) appears to fold more quickly via other three‐disulfide intermediates. The folding catalyst PDI increases dramatically both yields and rates of lysozyme refolding, largely by facilitating the conversion of des‐[76–94] to the native state. This suggests that acceleration of the folding rate may be an important factor in avoiding aggregation in the intracellular environment.
Prevalence of sclerosing cholangitis in adults with autoimmune hepatitis: A prospective magnetic resonance imaging and histological study

The development of sclerosing cholangitis (SC) is observed in up to 50% of children followed up for autoimmune hepatitis (AIH). In adults, the prevalence is less known, although a recent study found evidence of SC in 10% of AIH patients using magnetic resonance cholangiopancreatography (MRCP). The aim of this study was to assess prospectively the prevalence of SC in adults with AIH. Fifty‐nine consecutive patients with AIH diagnosed according to International Autoimmune Hepatitis Group score (women, 71%; mean age, 48 years; cirrhosis, 23%) underwent both MRCP and percutaneous liver biopsy. Twenty‐seven patients with cirrhosis of nonbiliary or non‐autoimmune etiology served as controls. Fourteen AIH patients (24%) showed mild MRCP abnormalities of intrahepatic bile ducts (IHBDs). None had abnormal common bile duct or convincing evidence of SC on MRCP or biopsy. A diagnosis of overlapping SC was nevertheless retained in one patient with MRCP abnormalities who subsequently developed symptomatic cholestasis despite corticosteroid therapy. Fibrosis score was the only independent parameter associated with bile duct abnormalities on MRCP (odds ratio 2.4; 95% confidence interval 1.4‐4.7) and the percentage of patients with IHBD MRCP abnormalities was not different among F3‐F4 AIH patients (n = 24) and cirrhotic controls (46% versus 59%; NS). Conclusion: In this cohort of adult patients with AIH, the prevalence of SC was much lower than previously reported (1.7%). Mild MRCP abnormalities of IHBD were seen in a quarter of patients, but these abnormalities resulted from hepatic fibrosis and not SC. In the absence of cholestatic presentation, MRCP screening does not seem justified in adult‐onset AIH. (HEPATOLOGY 2009.)
Carbon dioxide and methane dynamics in a human‐dominated lowland coastal river network (Shanghai, China)

Evasion of carbon dioxide (CO2) and methane (CH4) in streams and rivers play a critical role in global carbon (C) cycle, offsetting the C uptake by terrestrial ecosystems. However, little is known about CO2 and CH4 dynamics in lowland coastal rivers profoundly modified by anthropogenic perturbations. Here we report results from a long‐term, large‐scale study of CO2 and CH4 partial pressures (pCO2 and pCH4) and evasion rates in the Shanghai river network. The spatiotemporal variabilities of pCO2 and pCH4 were examined along a land use gradient, and the annual CO2 and CH4 evasion were estimated to assess its role in regional C budget. During the study period (August 2009 to October 2011), the overall mean pCO2 and median pCH4 from 87 surveyed rivers were 5846 ± 2773 μatm and 241 μatm, respectively. Internal metabolic CO2 production and dissolved inorganic carbon input via upstream runoff were the major sources sustaining the widespread CO2 supersaturation, coupling pCO2 to biogeochemical and hydrological controls, respectively. While CH4 was oversaturated throughout the river network, CH4 hot spots were concentrated in the small urban rivers and highly discharge‐dependent. The Shanghai river network played a disproportionately important role in regional C budget, offsetting up to 40% of the regional terrestrial net ecosystem production and 10% of net C uptake in the river‐dominated East China Sea fueled by anthropogenic nutrient input. Given the rapid urbanization in global coastal areas, more research is needed to quantify the role of lowland coastal rivers as a major landscape C source in global C budget.
MCMC Methods for Computing Bayes Factors: A Comparative Review

The problem of calculating posterior probabilities for a collection of competing models and associated Bayes factors continues to be a formidable challenge for applied Bayesian statisticians. Current approaches that take advantage of modern Markov chain Monte Carlo (MCMC) computing methods include those that attempt to sample over some form of the joint space created by the model indicators and the parameters for each model, others that sample over the model space alone, and still others that attempt to estimate the marginal likelihood of each model directly (since the collection of these is equivalent to the collection of model probabilities themselves). In this paper we review several of these methods, and subsequently compare them in the context of two examples, the rst a simple regression example, and the second a much more challenging hierarchical longitudinal model of the kind often encountered in biostatistical practice. We nd that the joint model-parameter space search methods perform adequately but can be diicult to program and tune, while the marginal likelihood methods are often less troublesome and require less in the way of additional coding. Our results suggest that the latter methods may be most appropriate for practitioners working in many standard model choice settings, while the former remain important for comparing large numbers of models, or models whose parameters cannot be easily updated in relatively few blocks. We caution however that all of the methods we compare require signiicant human and computer eeort, suggesting that less formal Bayesian model choice methods may ooer a more realistic alternative in many cases.
Task Assignment on Spatial Crowdsourcing (Technical Report)

Recently, with the rapid development of mobile devices and the crowdsourcing platforms, the spatial crowdsourcing has attracted much attention from the database community. Specifically, spatial crowdsourcing refers to sending a location-based request to workers according to their positions, and workers need to physically move to specified locations to conduct tasks. Many works have studied task assignment problems in spatial crowdsourcing, however, their problem definitions are quite different from each other. As a result, there is no work to compare the performances of existing algorithms on task assignment in spatial crowdsourcing. In this paper, we present a comprehensive experimental comparison of most existing algorithms on task assignment in spatial crowdsourcing. Specifically, we first give some general definitions about spatial workers and spatial tasks based on definitions in the existing works studying task assignment problems in spatial crowdsourcing such that the existing algorithms can be applied on same synthetic and real data sets. Then, we provide a uniform implementation for all the algorithms of task assignment problems in spatial crowdsourcing. Finally, based on the results on both synthetic and real data sets, we conclude the strengths and weaknesses of tested algorithms, which can guide further researches on the same area and practical implementations of spatial crowdsourcing systems.
Residential customer outage cost valuation for urban areas in Nepal

Utilities in most of the developing countries do not possess relevant information to evaluate the electricity supply outage cost incurred by the customers. This paper shows the significance of customer survey techniques to evaluate customer outage cost in developing countries in the era of restructuring and globalization. Residential customer surveys that are extensively used by utilities in the developed countries can not be directly adopted in developing countries. Relevant modifications that incorporate customer behaviour in the rapidly changing socio-economic characteristics in those nations must be adequately addressed. The results obtained using customer survey techniques are consistent with the figures anticipated and also indicate toward the need to carry out such surveys for other customer categories as well. The survey questionnaire is designed to obtain customer information to have uninterrupted power supply based on their willingness to pay (WTP), alternative actions and willingness to accept (WTA) monetary compensation for agreeing frequent supply interruptions. The outage cost evaluation is carried out using least square error method by a computer program developed in MATLAB platform.
Batch Performance for an Online Price

Batch learning techniques achieve good performance, but at the cost of many (sometimes even hundreds) of passes over the data. For many tasks, such as web-scale ranking of machine translation hypotheses, making many passes over the data is prohibitively expensive, even in parallel over thousands of machines [1]. Online algorithms, which treat data as a stream of examples, are conceptually appealing for these large scale problems. In practice, however, online algorithms tend to underperform batch methods, unless they are themselves run in multiple passes over the data [2].
Fast Color-Independent Ball Detection for Mobile Robots

This paper presents a novel scheme for fast color invariant ball detection in the RoboCup context. Edge ﬁltered camera images serve as an input for an Ada Boost learning procedure that constructs a cascade of classiﬁcation and regression trees (CARTs). Our system is capable to detect different soccer balls in the RoboCup and other environments. The resulting approach for object classiﬁcation is real-time capable and reliable.
Supervised endurance exercise training compared to home training after first lumbar diskectomy: a clinical trial.

OBJECTIVE We performed a randomised trial to evaluate if intensive supervised training of the back should be offered to all patients after a first lumbar diskectomy. METHODS Forty consecutive patients were, after a first lumbar diskectomy, randomly allocated to 2 groups undergoing "supervised training" twice a week for 3 months in an outpatient clinic or "home training" after 2 hours of instruction. RESULTS The two rehabilitation models both showed a significant effect on spinal mobility, isokinetic trunk flexion strength, isokinetic trunk extension strength and daily function. These improvements were unchanged at follow up 3 months later. The pain score remained unchanged, however, throughout the trial in both groups. No differences in effect between the two rehabilitation models could be found for any of the assessed parameters. Thirteen patients did not complete the trial, including 9 from the supervised endurance trained group, mainly because of increased pain and reprolaps (n = 4). Four patients dropped out of the home trained group, only one because of increased pain. The differences in drop-out rate and training side effects were, however, not statistically significant. CONCLUSION We conclude that it is not worthwhile to implement 3 months of supervised intensive endurance training as opposed to home training in all cases of first lumbar diskectomy, although a beneficial effect and better compliance might be found for a selected group of such patients.
JITTER FUNDAMENTALS Jitter — Understanding it , Measuring It , Eliminating It Part 1 : Jitter Fundamentals

I n data communications , once bit transfer rates exceed one gigabit-per-second, simply dealing with 1s and 0s is no longer sufficient. This situation is clearly the case with many of the new data transfer stan-concern themselves with the true nature of a circuit carrying binary information, realizing that it is, in fact, an analog circuit. This means that many parametric issues have become more important than ever. Among the parametric issues, jitter has risen to the top as one of the most significant and is therefore having a huge impact on the design, operation, and proof of many of today's products. This series of three articles is intended for engineers who design data transfer systems and components operating at over one gigabit-per-second and so must be concerned with the effects of jitter on their system's bit error rate (BER). This first article covers the fundamental of jitter, the kinds of jitter, its causes, the characteristics of individual jitter components and some measurement vantage points. Jitter isn't measured simply to create statistics, it is measured because jitter can cause transmission errors. For if jitter results in a signal being on the " wrong side " of the transition threshold at the sampling point, the receiving circuit will interpret that bit differently than the transmitter intended, causing a bit error, as depicted in Figure 1. Furthermore, as we will discuss in this and future articles, jitter measurements can aid in discerning the various kinds of jitter which, in turn, leads to their causes and to effectively diminishing their deleterious effect on circuit performance. Jitter can be defined as " the deviation of the significant instances of a signal from their ideal location in time. " To put it more simply, jitter is how early or late a signal transition is with reference to when it should transition. In a digital signal the significant instances are the transition (crossover) points. This applies whether the time reference is generated from the sampled data or is externally provided. These definitions allow for a number of ways of quantifying jitter, as noted next. Cycle-To-Cycle Jitter—The time differences between successive periods of a signal. Period Jitter—An RMS calculation of the difference of each period from a waveform average.
Rethinking adaptive capacity: A study of Midwestern U.S. corn farmers

Global climate change is one of the most significant challenges facing agriculture and society in the 21st century. In the Midwest, the projected trend toward more extreme rainfall has meant that farm-level responses are needed to maintain or increase crop yield and reduce soil erosion. On a local level, farmers are at the forefront of responding to environmental change. Thus, it is critical to understand their ability to take suitable actions for reducing risks and transforming agriculture to a more resilient system. Adaptive capacity is a term that is often used to describe farmers’ ability to access financial and technical resources. Although these are important attributes of farmers’ capacity, scholarship on human behavior has identified socio-cultural factors, such as perceived risk and capacity as strong predictors of farmers’ decision making. Therefore, our understanding of farmers’ true capacities is limited by our inability to comprehensively understand social and behavioral factors that influence their decisions to ignore, cope or adapt to climate change-related risks. In this dissertation, I attempt to address this gap by integrating social and behavioral theoretical frameworks and statistical modeling approaches to assess how variations in institutional and environmental conditions can influence farmers’ adaptive capacity and their decision to use adaptive management practices.
Genre structuring in a web-based groupware medium: the evolution of project progress report

Information Technology supported teaching and learning typically borrows many teaching practices and instruments from previous contexts. These typical practices or instruments can be classified into recognizable types or “genres”. There are different ways in which these genres cross the boundaries of action, voice or paper based techniques to their electronically provided alternates. This study applies the framework of “genre structuring” to explore the evolution of a project progressreporting mechanism, re-implemented in a web-based groupware application, and used in several different Information Technology courses over the last three years.