text large_stringlengths 384 2.05k | rank_avg float64 1 4.19k ⌀ | rank_max float64 1 8.21k ⌀ | rank_min float64 1 5.03k ⌀ | rank_median float64 1 4.21k ⌀ | rank_by_avgsim float64 1 4.19k ⌀ | avgsim_to_github float32 0.77 0.85 ⌀ | dataset large_stringclasses 1
value |
|---|---|---|---|---|---|---|---|
s, unlike for a linear operator, the non-existence of an inverse is not just due the set $\{ f^{-1}(0)\}$ which happens to be the only way a linear map can fail to be injective. Thus the map defined piecewise as $\alpha+2(1-\alpha)x$ for $0\leq x<1/2$ and $2(1-x)$ for $1/2\leq x\leq1$, with $0<\alpha<1$, is not inverti... | 801 | 395 | 1,479 | 843 | null | null | github_plus_top10pct_by_avg |
et(M)=4\gamma^3(\gamma-1)^9=4+2\gamma^3\ne 0$ and so we can use recover $a_\tau$ as before.
Generalization to more servers {#sec-kserver}
==============================
In this section we prove Theorem \[THM-kserver\]. As was mentioned in the introduction, we will allow the database symbols to belong to a slightly la... | 802 | 1,686 | 1,363 | 779 | 3,540 | 0.771672 | github_plus_top10pct_by_avg |
erturbations (a)–(c) described in Sec. \[sec:exper\]. For all results below the system without the varied antenna, corresponding to $\lambda=0$, is chosen as the reference, whereas for the perturbed system the coupling constant is $\lambda'=\lambda_{50\Omega}$, $\lambda_{\rm oe}$, or $\lambda_{\rm hw}$, depending on th... | 803 | 175 | 730 | 796 | 2,150 | 0.782256 | github_plus_top10pct_by_avg |
of size one, i.e. $\lrabs{\eta}=1$, we define $$\begin{aligned}
H(w) := \E{\zeta(w,\eta) \zeta(w,\eta)^T }
\numberthis\label{e:m0}\end{aligned}$$ as the covariance matrix of the difference between the true gradient and a single sampled gradient at $w$. A standard run of SGD, with minibatch size $b := \lrabs{\eta_k} $,... | 804 | 665 | 740 | 895 | 1,206 | 0.792764 | github_plus_top10pct_by_avg |
n</p>
</div>
<div class="col-md-3">
<p>Fourth column</p>
</div>
</div>
A:
use linear-gradient in body , giving your .container is the parent, and you won't have any wrapper around .container
Sorry that I'm bothering you, but what I meant was to place the image
like this
image.prntscr.com/image/78940c8115c9... | 805 | 6,332 | 98 | 122 | 33 | 0.834546 | github_plus_top10pct_by_avg |
is nontrivial in the total Hilbert space including unphysical degrees of freedom.
In any case, except for such an unphysical complexity, we have now understood how space-time supersymmetry is realized in superstring field theory, and therefore are ready to study various consequences of space-time supersymmetry[@Kishim... | 806 | 1,416 | 1,442 | 867 | null | null | github_plus_top10pct_by_avg |
ee bosons in the semi-classical limit, as anticipated. At fixed $kf^2$ and for each interaction vertex, the power of the coupling constant $f$ is equal to the number of structure constants that appear. Since we are interested in computing OPEs involving the currents and the primary fields, let us write these fields in ... | 807 | 1,326 | 1,489 | 899 | null | null | github_plus_top10pct_by_avg |
[$\frac{1}{4}(-1,3)$]{}; at ($.5*(D)+.5*(B)+(-1.5,.8)$) [$E_2$]{};
($.5*(B)+.5*(D)-(0,.75)$) circle \[radius=.1cm\]; at ($.5*(D)+.5*(B)-(-.25,.5)$) [$\frac{1}{3}(-1,4)$]{};
($.5*(F)+.5*(C)+(0,-1)$) node\[below=3\] [$-\frac{1}{30}$]{} – ($.5*(F)+.5*(C)+(0,1.5)$); at ($.5*(F)+.5*(C)+(-1.5,.5)$) [$\frac{1}{3}(-1,10)$]{... | 808 | 1,450 | 627 | 817 | 2,831 | 0.776712 | github_plus_top10pct_by_avg |
by other variables when $L_i$ is *of type* $\textit{I}^o$ (resp. *of type* $\textit{I}^e$), and so on.
From now on, we eliminate suitable variables based on Equations (\[ea20\]), (\[ea22\]), (\[24\]), (\[24’\]), (\[ea25\]), (\[ea27\]), and (\[ea32\]), the equations $\sum_{l=0}^{k_j}z_{j-l}^{\ast}+\sum_{l=0}^{k_j}
\bar... | 809 | 572 | 1,438 | 959 | 2,731 | 0.777451 | github_plus_top10pct_by_avg |
nonumber\end{aligned}$$
Moreover, we have the following relations,
$$\begin{aligned}
& & \mbox{exp} \left( \hat{b}^{ij}_+(u) \right)
: \mbox{exp} \left( \hat{b}^{i'j'}(v) \right) : \\
& &~~~~= \left( \frac{u-v-\frac{1}{2} \hbar}
{u-v +\frac{1}{2} \hbar} \right)^{\delta^{ii'} \delta^{jj'}}
: \mbox{exp} \left( \hat{b}^... | 810 | 385 | 959 | 869 | 4,001 | 0.768698 | github_plus_top10pct_by_avg |
re $k =|{\widehat{S}}| < n$. For the LOCO and prediction parameters, based on $\mathcal{D}_{1,n}$, we also compute $\widehat{\beta}_{{\widehat{S}}}$, any estimator of the projection parameters restricted to ${\widehat{S}}$. In addition, for each $j \in {\widehat{S}}$, we further compute, still using $\mathcal{D}_{1,n}$... | 811 | 329 | 701 | 849 | 2,471 | 0.779486 | github_plus_top10pct_by_avg |
; \\
\mathcal{X}_{i,2,3}(m)={}^tr_i\bar{a}_it_i+x_i+z_iu_i+\mathcal{P}^i_{2, 3}=\bar{d}_i=0
\end{array} \right.$$ and $$\begin{gathered}
\label{24'}
\mathcal{X}_{i,2,2}(m)=\bar{\gamma}_i+z_i+z_i^2+1/2\left({}^tm_{i-1, i}'h_{i-1}m_{i-1, i}'+{}^tm_{i+1, i}'h_{i+1}m_{i+1, i}'\right)+\\
\textit{ ... | 812 | 1,770 | 752 | 870 | 3,244 | 0.773793 | github_plus_top10pct_by_avg |
\frac{\nabla D(X)}{D(x)}} dx = \int_{0}^{x} \lrp{\frac{\nabla U(x)}{D(x)}} dx + \log D(x) - \log D(0)$. We can verify that $p^*(x) \propto e^{-V(x)}$ satisfies .
For a concrete example, let the potential $U(x)$ and the diffusion function $M(x)$ be defined as $$\begin{aligned}
& U(x) := \threecase{\frac{1}{2} x^2}... | 813 | 3,175 | 1,028 | 748 | 1,527 | 0.788615 | github_plus_top10pct_by_avg |
$ (resp. $g_{i+2, i}$) if $L_{i-2}$ (resp. $L_{i+2}$) is *of type* $\textit{I}^o$.
- $k_{i-2, i}$ (resp. $k_{i+2, i}$) is the $(n_{i-2}-1, n_i)^{th}$-entry (resp. $(n_{i+2}-1, n_i)^{th}$-entry) of the matrix $g_{i-2, i}$ (resp. $g_{i+2, i}$) if $L_{i-2}$ (resp. $L_{i+2}$) is *of type* $\textit{I}^e$.\
4. A... | 814 | 4,439 | 251 | 487 | 2,630 | 0.778255 | github_plus_top10pct_by_avg |
ality proposal in this example predicts that the dual is defined by a heterotic $E_8 \times E_8$ compactification on $[T^4/{\mathbb Z}_2]$, with $E_8$ bundle defined by ${\cal E}^* \otimes {\cal E}$, $\wedge^{\rm even} {\cal E}$, for ${\cal E} = {\cal O}^8$ on $T^4$, but such that ${\cal E}^* \otimes {\cal E}$ and $\we... | 815 | 765 | 1,147 | 771 | 2,098 | 0.782756 | github_plus_top10pct_by_avg |
114 116 0.0300
Only blood urea nitrogen differences met criteria for partitioning by season for reference intervals.
10.1371/journal.pone.0115739.t003
###### Hematology and plasma biochemical parameters that were significantly correlated with water temperature in ju... | 816 | 5,574 | 267 | 275 | null | null | github_plus_top10pct_by_avg |
silon}}$, then $$\begin{aligned}
W_1\lrp{p^*, p^y_{k\delta}} \leq 2\hat{\epsilon}
\end{aligned}$$ where $p^y_t := \Law(\by_t)$.
Let $\epsilon := \frac{\lambda}{16 (L+\LN^2)} \exp\lrp{-\frac{7\aq\Rq^2}{3}} \hat{\epsilon}$. Let $f$ be defined as in Lemma \[l:fproperties\] with the parameter $\epsilon$.
... | 817 | 1,544 | 780 | 835 | null | null | github_plus_top10pct_by_avg |
b \beta \int_{0}^{+\infty} (b z + c)^{2}
\exp{\left( - z^{\frac{1}{a}} \right)} dz \allowdisplaybreaks \\
&= (k_{1}^{2} + k_{2}^{2}) b^{3} \beta
\int_{0}^{+\infty} z^{2} \exp{\left( - z^{\frac{1}{a}} \right)} dz
+ (k_{1}^{2} - k_{2}^{2}) b^{3} \beta
\int_{0}^{c / b} z^{2} \exp{\left( - z^{\frac{1}{a}} \right)} dz ... | 818 | 4,054 | 795 | 613 | null | null | github_plus_top10pct_by_avg |
uence ${\mathscr{I}} \to {\mathbb{S}}$ of steps (usually ${\mathscr{I}}$ will be the natural numbers ${\mathbb{N}}$).
We revisit the three fundamental P’s (path, procedure, and process – §\[S:THREE\_P\]). A walk in step space decomposes into these three sequences: $\textrm{walk}_{\,i} = (\textrm{path}_{\,i}, \textrm{p... | 819 | 851 | 1,603 | 806 | null | null | github_plus_top10pct_by_avg |
to Appendix \[nc\] to get a first glimpse into why the case of $p=2$ is really different. Some of the ideas behind our construction can be seen in the simple example illustrated in Appendix \[cfot\].
Acknowledgements
----------------
This paper was initially the second half of [@C2]. Due to a huge number of pages an... | 820 | 435 | 370 | 886 | 2,050 | 0.783186 | github_plus_top10pct_by_avg |
0 0 1 0 0.25 0
Fatal 0 1 1 1 0 1 0 0 1 3 0.25 0.75
Cardiac events (n=2)
Fatal ... | 821 | 3,590 | 834 | 700 | null | null | github_plus_top10pct_by_avg |
cancer (*n* = 5), malignancies of the upper respiratory tract (*n* = 2), advanced melanoma (*n* = 2), Hodgkin\'s lymphoma (*n* = 1) and Merkel cell carcinoma (*n* = 1) ([@B7]--[@B15]). With respect to demographics, the patients were either of Asian (*n* = 6) or Caucasian (*n* = 5) origin, aged 49--87 years and predomi... | 822 | 713 | 887 | 1,186 | null | null | github_plus_top10pct_by_avg |
rans\] demonstrates that the desired result is obtained when the time scales are prolonged: With $T_{\rm ramp} = 200\,T$ and $T_{\rm pulse} = 1070\,T$, one has practically complete transfer.
It is, of course, also possible to employ the method outlined here to prepare the particle in superpositions of defect states. F... | 823 | 3,997 | 1,997 | 972 | null | null | github_plus_top10pct_by_avg |
ac{1-u^2}{u^2+1} & 0 \\
\mathcal{D}_u & 0 & 0 & 0 & 0 \\
\noalign{\bigskip}
\text{} & C_T'(u) & C_\Phi'(u) & C_R'(u) & C_u'(u) \\
\noalign{\smallskip} \hline \hline \noalign{\smallskip}
\mathcal{D}_T & -\frac{4 u}{\left(u^2+1\right)^2} & -\frac{2 u \left(u^2-3\right)}{\left(u^2+1\right)^2} & 0 & 0 \\
\mathcal{D... | 824 | 2,989 | 1,053 | 812 | null | null | github_plus_top10pct_by_avg |
will be left as a free constant.
Note that the integrand in eq. (\[Pf\]) is precisely of the form shown in eq. (\[projection\]). In fact, on large scales (small $k_\parallel$ as well as $k$ i.e. small compared to $k^s_\parallel$, $1/b_{T_0}$ and $k_F$), modulo multiplicative factors, it reduces to the famous Kaiser [... | 825 | 2,025 | 1,527 | 887 | 2,595 | 0.7786 | github_plus_top10pct_by_avg |
th order F\^[(0)]{}\_[abc]{} \_a A\_[bc]{} - \_b A\_[ac]{}. The first term of (\[3-point-1\]) comes from the Lie algebra structure of this generalized YM theory. The second term arises due to the field-dependent inner-product of the Lie algebra.
Near the end of Sec.\[heuristic\], we discussed how the formulation of gr... | 826 | 188 | 1,559 | 958 | null | null | github_plus_top10pct_by_avg |
d\]) we get the set of winning values given in Table 1.
s, t Alice, Bob
------ ------------
14 01, 10, 22
15 01, 10, 22
17 00, 12, 21
24 02, 11, 20
25 01, 10, 22
28 02, 11, 20
34 00, 11, 22
37 00, 11, 22
38 02, 10, 21
41 01, 10, 22
42 02, 11, 20
... | 827 | 4,241 | 1,230 | 532 | 3,711 | 0.770535 | github_plus_top10pct_by_avg |
{r^2}{2}}{r\leq \R}
{\frac{\R^2}{2} + \R (r-\R) + \frac{(r-\R)^2}{2}- \frac{(r-\R)^3}{3\R}}{r\in[\R,2\R]}
{\frac{5\R^2}{3} + \R(r-2\R) - \frac{(r-2\R)^2}{2} + \frac{(r-2\R)^3}{12\R}}{r\in [2\R,4\R]}
{\frac{7\R^2}{3}}{r\geq 4\R]}
\end{aligned}$$ Then
1. $\tau'(r) \in [0,... | 828 | 2,707 | 911 | 841 | null | null | github_plus_top10pct_by_avg |
k National University in 2015.
Peer review under responsibility of King Saud University.
{#f0005}
![Morphology of *S. pyogenes* under transmission electron microscope grown under (A) norma... | 829 | 95 | 1,756 | 1,140 | null | null | github_plus_top10pct_by_avg |
is therefore a function indexed by a directed set. We adopt the convention of denoting nets in the manner of functions and do not use the sequential notation $\chi_{\alpha}$ that can also be found in the literature. Thus, while every sequence is a special type of net, $\chi:\!\mathbb{Z}\rightarrow X$ is an example of ... | 830 | 2,931 | 1,954 | 855 | 2,750 | 0.777292 | github_plus_top10pct_by_avg |
F\_j, V\_[1,j]{}(0)=0, where $(V_{1,j}(\eta))(x,\omega)=V_{1,j}(x,\omega,\eta)$ and $(F_j(\eta))(x,\omega)=F_j(x,\omega,\eta)$. The $C^0$-semigroup $G(\eta)$ generated by $B_0-\Sigma_j$ is (by the Trotter’s formula) given by \[infgen\] (G()h)(x,) = e\^[-\_0\^\_j(x-,) d]{}H(t(x,)-)h(x-,). Hence the solution $V_{1,j}$ is... | 831 | 203 | 1,453 | 980 | null | null | github_plus_top10pct_by_avg |
ments, namely dynamic graph and hypergraph models. In order to measure the dynamicity, [we introduce]{} the notion of *pair visibility*. For a pair $\{i,j\}$ of distinct vertices, the *visibility* of $\{i, j\}$, denoted by ${\ensuremath{\operatorname{\mathtt{vis}}(i,j)}}$, is the number of rounds $t\in\{1,\ldots, n\}$ ... | 832 | 637 | 1,297 | 889 | 1,482 | 0.789013 | github_plus_top10pct_by_avg |
definition. Read more about it in this blog article
Q:
Changing a property modifier when merging an interface
The Window interface has a few properties that are readonly:
interface Window extends ... {
// ...
readonly innerHeight: number;
readonly innerWidth: number;
// ...
}
I get that those cannot reall... | 833 | 4,239 | 11 | 769 | 324 | 0.813367 | github_plus_top10pct_by_avg |
in $B\otimes_AR$. Thus there are exactly $(n_i-2)$ independent linear equations among the entries of $v_i'$ and $r_i'$.
3. The $(1,3)$-block is $$\label{ea8}
e_i'=\pi(- {}^ty_i'+a_it_i').$$ This is an equation in $B\otimes_AR$. By letting $e_i'=e_i=0$, there are exactly $(n_i-2)$ independent linear equa... | 834 | 2,070 | 1,370 | 854 | null | null | github_plus_top10pct_by_avg |
3---S6 90.68 (4) C40---C41---H41 119.7
S5---Ag3---S6 87.08 (4) C41---C42---C43 120.5 (5)
P4---Ag3---W2 117.46 (3) C41---C42---H42 119.8
P3---Ag3---W2 104.71 (3) C43---C42---H42 119.8
S5---Ag3---W2 45.48 (2) C42---C43---C44 119.6 (4)
S6---Ag3-... | 835 | 2,272 | 2,768 | 1,113 | null | null | github_plus_top10pct_by_avg |
and Innovation project TEC 2012-32336, and by the Generalitat de Catalunya research support program SGR-1202. This work is also partially supported by the Secretariat for Universities and Research (SUR) and the Ministry of Economy and Knowledge through AGAUR FI-DGR 2012 and BE-DGR 2012 grants (M. M.)
[^1]: Marc Manzan... | 836 | 65 | 1,461 | 1,232 | null | null | github_plus_top10pct_by_avg |
eft( \left( \det {\cal E}_1^{\alpha} \right)
\left( \det T_1^{\alpha} \right)^{-1} \right)^{+1/6} \otimes
\left( \left( \det {\cal E}_2^{\alpha} \right) \left( \det T_2^{\alpha}
\right)^{-1} \right)^{-1/6} ,\end{aligned}$$ and $$\begin{aligned}
{\cal F}_+^{\alpha^{-1}} & = & \left( \left( \det {\cal E}_1^{\alpha^{-1}... | 837 | 1,795 | 1,613 | 860 | null | null | github_plus_top10pct_by_avg |
18
FP4_Bowtie 0.58 0.331 8 0.60 0.356 10 0.330
FP4_MAQ 0.58 0.335 9 0.60 0.361 12 0.334
FP4_Soap2 0.58 0.333 9 0.60 0.357 11 0.... | 838 | 2,366 | 1,632 | 983 | null | null | github_plus_top10pct_by_avg |
isits following RFVTA is presented in Figure [1](#F1){ref-type="fig"}. Of the 135 women satisfying all inclusion criteria and treated at baseline, 11 subjects had interfering circumstances unrelated to the procedure (pregnancy, lack of menses, and Hashimoto's Disease) that could have influenced bleeding assessments pos... | 839 | 1,024 | 965 | 1,048 | null | null | github_plus_top10pct_by_avg |
erature [@BGMP].
For the comparison we have computed the present flow with the zero-temperature running coupling in Fig. \[fig:alpha\] for all temperatures. This mimics the approximation used in [@Braun:2007bx], which implicitly relies on the zero-temperature running coupling $\alpha_s$. We also remark that the quanti... | 840 | 132 | 969 | 838 | null | null | github_plus_top10pct_by_avg |
yperparameters), and the small portion was used to train the calibrators. The 3 calibrators trained in the inner 3-folds were used to predict the corresponding test partition, and their predictions were averaged in order to obtain better estimates of their performance with the 7 different metrics (accuracy, Brier score... | 841 | 435 | 364 | 527 | null | null | github_plus_top10pct_by_avg |
erimental situation shall now be mapped onto the theory derived in the preceding subsection. Though the calculation is straightforward, and similar approaches can be found elsewhere [@stoe02c], it is repeated here for the reader’s convenience. Let us start with the expression of the scattering matrix in terms of Wigner... | 842 | 4,295 | 649 | 677 | 846 | 0.798998 | github_plus_top10pct_by_avg |
under arbitrary model selection rules without relying on sample splitting. We omit the details.
### Confidence sets for the projection parameters: Normal Approximations {#confidence-sets-for-the-projection-parameters-normal-approximations .unnumbered}
We will now derive confidence intervals for the projection parame... | 843 | 2,971 | 1,262 | 828 | 3,618 | 0.771206 | github_plus_top10pct_by_avg |
ution to in $D$ by $$u(x) =\pi^{-2} \sin(\pi \alpha/2) \int_{D^{\texttt{c}}} \left( \frac{1-|x|^2} {|y|^2-1} \right)^{\alpha/2} \frac{1} {|y-x|^2} \exp(-|x-y|^2) \,{\rm d}y,
\qquad x\in D.
\label{eq:ana_T4.4}$$ This integral can be computed numerically via a quadrature approximation... | 844 | 1,629 | 2,720 | 891 | 943 | 0.797096 | github_plus_top10pct_by_avg |
{m,n} \phi^{(0)}_{m-1,n} + \phi^{(1)}_{m+1,n} \phi^{(1)}_{m,n} \phi^{(1)}_{m-1,n}}{1+\phi^{(0)}_{m+1,n}\phi^{(0)}_{m,n} \phi^{(0)}_{m-1,n} + \phi^{(1)}_{m+1,n} \phi^{(1)}_{m,n} \phi^{(1)}_{m-1,n}} .
\end{gathered}$$ We also have the master symmetry (\[eq:phi-sys-msym\]), which can be written $$\begin{gathered}
\par... | 845 | 1,536 | 1,258 | 989 | null | null | github_plus_top10pct_by_avg |
N_\phi} \Theta_{ijk} e^{-2\pi \sqrt{-1}jm/N_\phi},$$ and similarly for ${\cal G}$ and $\sigma$. Then, Equation can be cast into a more compact form $$\label{eq:gpot_by_discrete_green_fft}
\Theta^m_{ik} = \sum_{i'=0}^{N_R+1}\sum_{k'=0}^{N_z+1}{\cal G}^m_{i,i',k-k'} \sigma^m_{i'k'}{\cal V}_{i'}.$$ Since $\sigma$ is non... | 846 | 2,523 | 1,435 | 922 | null | null | github_plus_top10pct_by_avg |
ant $C > 0$ such that $$\label{eq:loco.coverage1}
\inf_{w_n \in \mathcal{W}_n} \inf_{P \in \mathcal{P}_n^{\mathrm{LOCO}}} \mathbb{P} \left(
\gamma_{{\widehat{S}}} \in \widehat{D}_{{\widehat{S}}} \right) \geq 1 - \alpha - C
\left(
\mathrm{E}_{1,n} + \mathrm{E}_{2,n} \right)- \frac{1}{n},$$ and $$\l... | 847 | 3,928 | 395 | 660 | null | null | github_plus_top10pct_by_avg |
adding these constraints to the pre- and postcondition, we obtain the following implication.
- $\forall M,N \in {{\mathbb{Z}}}: ~M > N, ~N \in Dom_N, ~M \in Dom_M \Longrightarrow $\
$~~~~~~~~~~~M+1>N, ~N \in Dom_N, ~M+1 \in Dom_M$
Representing these domains by symbolic coefficients yields the following implicat... | 848 | 4,182 | 1,469 | 536 | 1,437 | 0.789577 | github_plus_top10pct_by_avg |
0.340 0.364 0.366 0.356 0.372
mMSE 0.400 0.352 0.384 0.416 0.368 0.356 0.376
BLB($n^{0.6}$) 0.000 0.000 0.000 0.000 0.002 0.000 0.002
BLB($n^{0.8... | 849 | 5,758 | 234 | 361 | null | null | github_plus_top10pct_by_avg |
i,L}).\end{aligned}$$ Recall the definition of ${b^{\chi}} $ in Eq. .
Let $i\in I$.
\(i) Let $m\in {\mathbb{N}}$. The following are equivalent.
- $E_i^m=0$ in $U(\chi )$,
- $F_i^m=0$ in $U(\chi )$,
- $m\ge {b^{\chi}} ({\alpha }_i)$.
\(ii) Let ${\Bbbk }[E_i]$ and ${\Bbbk }[F_i]$ be the subalgebras of $U(\chi... | 850 | 2,632 | 754 | 826 | 4,139 | 0.767822 | github_plus_top10pct_by_avg |
}} , \nabla_a \right]{\bf t}=0,
\label{eq:commutation-isometry-covariant}$$ where $\bf t$ can be a scalar, vector, or tensor. To prove Eq. , one can start by showing the commutation relations for $\bf t$ being a 0-form (which follows immediately from Cartan’s magic formula for a 0-form) and a one-form, then use the Lei... | 851 | 3,421 | 1,729 | 759 | null | null | github_plus_top10pct_by_avg |
O^!}) (\vec X;
\varnothing )^{-1}\big)$. This implies equation .
As for equation (\[Hi<0\]), we will use an induction that shows that every closed element in $\textbf{D}(\widehat{\mathcal O^!})
(\vec X;\varnothing)^{-r}$, for $r\geq 1$ is also exact. The argument will use an induction which slides all of the “full”... | 852 | 1,674 | 505 | 902 | 567 | 0.805451 | github_plus_top10pct_by_avg |
N, then you can apply some of the other parsing techniques suggested (use the Java StringTokenizer or the String.split() method as others here have suggested if it's known to be separated only by spaces). That assumes that you can make assumptions (eg. the first element in the resulting array is the firstName,the last... | 853 | 5,032 | 124 | 690 | 428 | 0.810054 | github_plus_top10pct_by_avg |
gma_Y)$ with $$\Delta = \max_{i,j} | \Sigma_X(j,k) - \Sigma_Y(j,k)|$$ Let $\underline{\sigma}^2 = \max\{ \min_j \Sigma_X(j,j) ,
\min_j \Sigma_Y(j,j) \}$. Then, there exists a universal constant $C>0$ such that $$\sup_{t \in \mathbb{R}^p} \left| \mathbb{P}( X \leq t) -
\mathbb{P}( Y \leq t) \right| \leq C \fra... | 854 | 564 | 981 | 904 | 1,751 | 0.786026 | github_plus_top10pct_by_avg |
udo data from unsupervised machine translation is especially effective for BWEs because (1) the pseudo data makes the source and target corpora (partially) parallel; (2) the pseudo data reflects some nature of the original language that helps learning similar embedding spaces between the source and target languages.'
a... | 855 | 374 | 467 | 882 | 1,469 | 0.789176 | github_plus_top10pct_by_avg |
he robot’s base. The distance from the mass centre of a link to a joint is denoted as $k_i$ while the joint angle between a link and the base or its preceding link is denoted as $\theta_i$.
![Dual arm robot modelling[]{data-label="fig1"}](model.png){width="0.8\linewidth"}
![Operational motions of dual arm robot[]{dat... | 856 | 4,184 | 1,292 | 550 | 3,113 | 0.774786 | github_plus_top10pct_by_avg |
ho_x}{df^*\rho_{F(x)}}(\xi) \ , \xi \in \partial X.$$ and let $K_x \subset \partial X$ denote the set where the function $u_x$ achieves its maximum. In [@biswas6], it is shown that for any $x \in X$, there exists a probability measure $\mu_x$ on $\partial X$ with support contained in $K_x$ such that $\mu_x$ is balanced... | 857 | 1,227 | 1,288 | 935 | 1,880 | 0.784739 | github_plus_top10pct_by_avg |
[08:51:03:206]: Note: 1: 1334 2: FailingFile 3: cab1.cab
Error 1334. The file 'FailingFile' cannot be installed because the file cannot be found in cabinet file 'cab1.cab'. This could indicate a network error, an error reading from the CD-ROM, or a problem with this package.
MSI (s) (88:54) [08:51:04:317]: Product: M... | 858 | 568 | 121 | 383 | 434 | 0.809843 | github_plus_top10pct_by_avg |
'[@thornley]'
- '[@dpj]'
- '[@doherty95]'
- '[@lph320]'
- '[@shields]'
- '[@vanzi]'
- '[@vr]'
- '[@chad]'
- '[@fs-m82]'
- '[@lph328]'
- '[@seaquist]'
- '[@sb]'
- '[@chip]'
- '[@guseva]'
- '[@schmutz]'
- '[@lejeune]'
- '[@kurtz]'
- '[@hanson]'
- '[@depree]'
- '[@garcia]'
- '[@btk]'
- '[@thb]'
- '[@kj99; @vjc]'
- '[@ccm... | 859 | 1,674 | 2,149 | 1,123 | null | null | github_plus_top10pct_by_avg |
e specific properties of GMAX0505. The structure of GMAX0505 is designed for visible light. In particular, its advanced light pipe structure optimizes the response to visible light as described in Yokoyama et al.[@Yokoyama2018] We applied it for x-ray imaging and polarimetry for the first time. Although Yokoyama et al.... | 860 | 47 | 422 | 1,005 | null | null | github_plus_top10pct_by_avg |
places protoset $G_\heartsuit^{(1)} = \tilde{V}({\mathit{s}}_{\text{crux}})$.
For a discussion of protoset $G_\heartsuit^{(n)}$ in context of the Cartesian product, see Appendix §\[D:PROTOSET\].
### Partial order {#S:CONE_ORDER}
Membership in a converse iterative operator induces a partial ordering:
Let ${\mathbb{... | 861 | 1,345 | 1,463 | 974 | 1,858 | 0.784994 | github_plus_top10pct_by_avg |
$. So far, we do not have uniform description for $\rho_{{\mbox{\boldmath $\alpha$}}}(s_i)$. So we define $\rho_{{\mbox{\boldmath $\alpha$}}}(s_1)$ and $\rho_{{\mbox{\boldmath $\alpha$}}}(s_2)$ one by one.
First we define $\rho_{{\mbox{\boldmath $\alpha$}}}(s_1)$. For tableaux $p_1$ and $p_2$ of $\mathbb{T}({\mbox{\bo... | 862 | 1,872 | 1,760 | 963 | 1,890 | 0.784663 | github_plus_top10pct_by_avg |
ec(%)** **F1(%)** **T(ms)** **Pre(%)** **Rec(%)** **F1(%)** **T(ms)** **Pre(%)** **Rec(%)** **F1(%)** **T(ms)** **Pre(%)** **Rec(%)** **F1(%)** **T(ms)**
**SDD-R** 89.51 48.75 63.12 266.77 21.97 **99.38** 35.98 11.12 6.67 ... | 863 | 3,190 | 838 | 684 | null | null | github_plus_top10pct_by_avg |
--C37 119.0 (4)
S7---W2---Ag4 60.14 (3) C33---C32---P5 118.1 (3)
S5---W2---Ag4 56.25 (3) C37---C32---P5 122.8 (3)
S8---W2---Ag3 112.82 (4) C32---C33---C34 120.8 (4)
S6---W2---Ag3 58.26 (3) C32---C33---H33 119.6
S7---W2---Ag3 137.85 (3) C34-... | 864 | 3,963 | 2,119 | 862 | null | null | github_plus_top10pct_by_avg |
$D(i,j)$ is the rate of hopping attempts from site $i$ to $j$ and depend on the investigated model. The sum runs over all $N$ pairs of nearest-neighbors of the lattice. Let $n_i$ be the number of lateral bonds of site $i$ and $n^\text{max}_i$ the largest number of bonds among the nearest-neighbors of $i$. For the WV mo... | 865 | 532 | 770 | 1,060 | 3,120 | 0.774733 | github_plus_top10pct_by_avg |
right|&\ge\frac{|AH|}{|X_1|\cdots|X_\ell|}\\
&\ge\frac{|AH|}{\exp(e^{O(s)}\log^{O(1)}2K)^\ell}\\
&\ge\frac{|AH|}{\exp(e^{O(s^2)}\log^{O(s)}2K)}.\end{aligned}$$ In particular, setting $Q_i=\{u_i^{-1},1,u_i\}$ for $i=1,\ldots,\ell$, we have $$\left|H\prod\{P_1,\ldots,P_k,Q_1,\ldots,Q_\ell\}\right|\ge\frac{|AH|}{\... | 866 | 245 | 820 | 937 | 2,068 | 0.783067 | github_plus_top10pct_by_avg |
. (). . . , , & (). , [ ** ]{}, . , , , & (). . , [ ** ]{}, . , , , , , , , , , & (). . , [ ** ]{}, . (). . , [ ** ]{}, . , , , , & (). . , [ ** ]{}, . (). . , [**]{}, . , & (). . , [**]{}, . , & (). . , [ ** ]{}, . , & (). . , [**]{}, . , & (). . , [ ** ]{}, . , , , & (). . , [ ** ]{}, . , , , , , , , & (). . , [ ** ]... | 867 | 2 | 2,481 | 971 | null | null | github_plus_top10pct_by_avg |
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------... | 868 | 3,148 | 1,796 | 940 | null | null | github_plus_top10pct_by_avg |
P0C0L4 Complement C4-A 2219.29 76.26 192.7 7.08
P00734 Prothrombin 2011.89 71.54 70.0 5.90
P19823 Inter-alpha-trypsin inhibitor heavy chain H2 1452.50 55.81 106.4 6.86
P19827 Inter-... | 869 | 4,438 | 709 | 572 | null | null | github_plus_top10pct_by_avg |
ing filtration with 11 μm filter.
Accession Description Score Coverage MW \[kDa\] calc. pI
----------- ---------------------------------------------- --------- ---------- ------------ ----------
P00734 Prothrombin 2458.17 67.2... | 870 | 5,153 | 262 | 284 | null | null | github_plus_top10pct_by_avg |
ition of the relationship between cause and effect in combination with the small number of included subjects. Also, the measurement of other markers of oxidative stress was unavailable.
V.R.: research plan, statistics, data collection and manuscript writing; V.K.: hemodynamic measurements and Echo-cardiographical asse... | 871 | 887 | 1,697 | 990 | null | null | github_plus_top10pct_by_avg |
(\lambda_{m} -\lambda_{k} ) },
\label{S-alpha-beta-0th-final}\end{aligned}$$ and the oscillation probability by $P(\nu_\beta \rightarrow \nu_\alpha) = \vert S_{\alpha \beta}^{(0)} \vert^2$.
Finally, armed with the solution , we can also calculate all higher order terms in oscillation probability for e.g. those in eq.... | 872 | 438 | 1,557 | 1,004 | null | null | github_plus_top10pct_by_avg |
ow a surface abundance about 0.2 - 0.3 dex lower than the predicted one. A possible way to improve the agreement with these stars is to adopt an initial lithium abundance of about $\epsilon_\mathrm{Li} \approx 3$. However, this method does not improve the agreement with the low-mass stars, a problem still largely discu... | 873 | 446 | 400 | 861 | 1,567 | 0.788182 | github_plus_top10pct_by_avg |
elta_{K} - h_{i} ) (\Delta_{L} - h_{i} ) ( h_{j} - h_{i} )^2 } e^{- i h_{i} x}
\nonumber \\
&-&
\frac{ 1 }{ (\Delta_{K} - h_{j} )^2 (\Delta_{L} - h_{j} )^2 ( h_{j} - h_{i} )^2 }
\biggl\{
3 h_{j}^2 - 2 h_{i} h_{j} - \left( 2 h_{j} - h_{i} \right) (\Delta_{K} + \Delta_{L} ) + \Delta_{K} \Delta_{L}
\biggr\}
e^{- i ... | 874 | 302 | 1,440 | 999 | null | null | github_plus_top10pct_by_avg |
----
T~0~ WT 1 47 \*^1^ 4: 100 0 60.0
T~0~ 1 71 \*^1^ 4: 100 100 ... | 875 | 4,592 | 921 | 411 | null | null | github_plus_top10pct_by_avg |
Q:
Reusing react components across projects
I want to split my web project into three: front-end, back-end and super-admin.
What is the best way to re-use the components across code bases? Npm packages? That seems hard to maintain:
Open component dev package
Make changes
Push changes
Tag version
Update all projects
... | 876 | 1,425 | 357 | 833 | 2,137 | 0.782452 | github_plus_top10pct_by_avg |
Usually one uses weighted or toric blow-ups with smooth center as a tool for finding embedded $\Q$-resolutions. Here we will briefly discuss weighted blow-ups in the surface case $\pi: \widehat{X} \to X$ at a point $P\in X=\frac{1}{d}(p,q)$ with respect to $w = (a,b)$. Consider $$\hat X:=\{((x,y),[u:v]_w)\in \CC^2\tim... | 877 | 358 | 886 | 863 | 2,691 | 0.777837 | github_plus_top10pct_by_avg |
\nonumber \\
S_{Sa} &=&
\left( Z X \right) \hat{S}_{aa} (U X)^{\dagger} + \left( Z X \right) \hat{S}_{aS} W^{\dagger} +
V \hat{S}_{Sa} (U X)^{\dagger} + V \hat{S}_{SS} W^{\dagger},
\nonumber \\
S_{SS} &=&
\left( Z X \right) \hat{S}_{aa} \left( Z X \right)^{\dagger} + \left( Z X \right) \hat{S}_{aS} V^{\dagger} + ... | 878 | 3,855 | 382 | 680 | null | null | github_plus_top10pct_by_avg |
ch that for every $\kappa \in {\mathbb{R}}$, $p>1$ and $f\in W^{q,k,p}({\mathbb{R}}^{d})$, $$\underline{C}_{q}\Vert \psi _{\kappa }|f|_{q}\Vert _{p}\leq \Vert f\Vert
_{q,\kappa ,p}\leq \overline{C}_{q}\Vert \psi _{\kappa }|f|_{q}\Vert _{p};
\label{NOT4a}$$
- for every $q\in {\mathbb{N}}$ and $p>1$ there exis... | 879 | 517 | 1,044 | 976 | null | null | github_plus_top10pct_by_avg |
where $\vartheta$ denotes the normalized spatial angle. The normalized spatial angle is related to the physical AOA or AOD $\theta\in\left[-\pi/2,\pi/2\right]$ by $
\vartheta={d\sin(\theta)}/{\lambda},
$ where $d$ denotes the antenna spacing and $\lambda$ denotes the wavelength.
We assume that $N_{1,{\mathrm{cl}}}=... | 880 | 3,665 | 1,299 | 894 | 1,900 | 0.784593 | github_plus_top10pct_by_avg |
P-value log~2~ (fold-change)
----------- ------------- ----------------------
FABP4 0.001621719 −2.100023748
CMAHP 0.024414059 −1.066127776
ITM2A 0.016922069 −1.060957028
CA4 0.003105875 −1.030691864
FAM189A2 0.001993414 −1.000814956
MPPED2 0.007206792 ... | 881 | 1,841 | 751 | 979 | null | null | github_plus_top10pct_by_avg |
)|<\epsilon$ if $O$ is small and $|\lambda-\lambda_i|\leq \delta$. This means that, up to a point $\lambda=\lambda_i+\delta'$ with $\delta'<\delta$, the value of $\theta_\Lambda(\lambda)$ does not explode. Choose $\lambda_i<\lambda_1<\lambda_i+\delta'$, then $\lambda_e+\Delta\lambda_e>\lambda_1$ for all the curves para... | 882 | 285 | 883 | 994 | null | null | github_plus_top10pct_by_avg |
e{k}_{i+2, i})_2^2+ (\tilde{k}_{i+2, i})_1\cdot (\tilde{k}_{i+2, i})_1'\right)
& \quad \textit{if $L_{i+2}$ is of type $I^e$} \end{array}\right.\\
+ \left(\delta_{i-3}'(\tilde{k}_{i-3, i})_1^2+ \delta_{i+3}'(\tilde{k}_{i+3, i})_1^2\right)+
\left(\delta_{i-4}(\tilde{k}_{i-4, i})_1^2+ \delta_{i+4}(\tilde{... | 883 | 3,918 | 783 | 557 | 2,237 | 0.781511 | github_plus_top10pct_by_avg |
we add the constraint on the maximum of the coefficients.
General $\ell_1$ minimization problem to promote sparsity {#l1}
---------------------------------------------------------
In addition to the number of connected components, we assume that we know one representative of each component i.e. a node belonging to t... | 884 | 2,235 | 1,610 | 859 | 3,155 | 0.77444 | github_plus_top10pct_by_avg |
ome new data, which supports our earlier findings.
The paper is organized as follows. Section \[sec:intro\] introduces notations. Section \[sec:value\] shows that the distribution of traded volume/value is not universal, and it is not in the Levy stable regime as suggested by Ref. [@gopi.volume]. Section \[sec:correl\... | 885 | 234 | 998 | 741 | null | null | github_plus_top10pct_by_avg |
mas está desse jeito. Assim que o app é iniciado, ele verifica a permissão chamando a classe Permissao. Se o usuário aceitar, o app inicia e se ele recusar o app fechar com uma mensagem informando que é preciso aceitar as permissões. Até ai tudo bem, porém se ele aceitar a permissão o app só funciona se ele fechar e ab... | 886 | 872 | 140 | 332 | 3,032 | 0.775327 | github_plus_top10pct_by_avg |
round 6 and 7 MeV are consistent between the two calculations. The energy-weighted sum ($1.867\times10^{4}$MeV$\cdot$fm$^{4}$) overestimates by about 13.9% the EWSR value ($1.638\times 10^{4}$MeV$\cdot$fm$^{4}$). The overshooting of the EWSR for the isoscalar quadrupole mode in the LM approximation was pointed out in R... | 887 | 668 | 1,422 | 985 | 1,694 | 0.786718 | github_plus_top10pct_by_avg |
t.
Standard tools {#sec:prelim}
==============
In this section we record various standard results relating to sets of small doubling and approximate groups. This material is likely to be familiar to experts in the subject, who may therefore decide to skip straight to \[sec:details\].
\[lem:slicing\] Let $K,L\ge1$ an... | 888 | 932 | 1,061 | 885 | 3,866 | 0.769633 | github_plus_top10pct_by_avg |
)\right]\;.
\nonumber\\\end{aligned}$$ The process of relaxation from the initial state can be followed by monitoring the subsystem observables $\hat{\sigma_z}$, which in the adiabatic basis reads $$\mbox{\boldmath$\sigma$}_z=\frac{1}{1+G^2}\left(
\begin{array}{cc} 2G & 1-G^2 \\ 1-G^2 & -2G\end{array}\right)\;.$$
The ... | 889 | 1,020 | 1,350 | 1,000 | null | null | github_plus_top10pct_by_avg |
fferent typically by $3-4$ orders of magnitude, we increase the radial cell size $\Delta
r$ with the fixed size ratio $\Delta r_i/\Delta r_{i-1}$ $(>1)$. We set $\Delta r_1 = 0.1 R_{\mathrm{in}}$ at the inner boundary. The grids in the angular direction are homogeneously distributed over $0<\theta<90^\circ$, and thus t... | 890 | 1,139 | 1,581 | 917 | null | null | github_plus_top10pct_by_avg |
ls. However, a difference in estimated firing behavior occurs at the 120mN response level whereby the SMC-MUNE procedure obtained two different model fits; MU1+MU4 in R10 and MU2+MU3 in R50. As a consequence, the estimated excitation range for MU1 in R50 is unusually large, leading to a relatively flat excitability cur... | 891 | 1,819 | 1,432 | 1,104 | null | null | github_plus_top10pct_by_avg |
\-
A/C 31 (56.4) 39 (52.7) 1.19 (0.57, 2.49) A/C 39 (52.0) 5 (41.7) 2.02 (0.58, 7.05)
C/C 20 (36.3) 30 (40.5) 0.8905 1 C/C 27 (36.0) 7 (58.3) 0.2255 1
A/A + A/C ... | 892 | 4,580 | 517 | 471 | null | null | github_plus_top10pct_by_avg |
two closely spaced peaks: $\mathrm{F}_1=3055.1$, $\mathrm{F}_2=3258.4$, $\mathrm{F}_3=3284.1$ and $\mathrm{F}_4=4780.6\,\mu$Hz. Similarly to the case of G 207-9, no further results of time series photometric observations have been published up to now.
### Konkoly observations {#sect:lp133freq}
We found four recurrin... | 893 | 927 | 2,986 | 1,086 | null | null | github_plus_top10pct_by_avg |
*r + r - 159. Give j(m(h)).
-26*h
Let y(a) = -3*a**2 - 19*a - 910. Let d(s) = s**2 + 6*s + 303. Let x(i) = -19*d(i) - 6*y(i). Let p(h) = 3*h**2. What is p(x(u))?
3*u**4 + 1782*u**2 + 264627
Let u(g) = -2*g**2. Let r be (-138)/(-8) - ((-7)/4 + 2). Let t(d) = 57*d**2 - 43 + 19*d + 43 - r*d. Give u(t(m)).
-6498*m**4 - 456... | 894 | 105 | 464 | 942 | null | null | github_plus_top10pct_by_avg |
maly probability, SDD-R can be also optimized by ranking all data collections according to their divergence value and select first $n \cdot \alpha$ ones with highest values as anomalies.
Evaluation {#sec:evaluation}
==========
Our algorithm was implemented and interpreted in Python 3.5.2. All experiments were tested ... | 895 | 355 | 889 | 930 | 1,353 | 0.790567 | github_plus_top10pct_by_avg |
result in this article.
\[uppercondition\] For an upper subsemigroup $S$ of $\mathcal{B}$, the following are equivalent:
$(i)$ $S$ is a left I-order in $\mathcal{B}$;
$(ii)$ $R_1 \subseteq S$.
Moreover, writing $S$ as $S=F_{D}\cup\bigcup_{i\in I} S_{i}$, we have $R_1 \subseteq S$ if and only if $0\in I, \ d=1$ and... | 896 | 1,307 | 685 | 1,019 | 3,836 | 0.769777 | github_plus_top10pct_by_avg |
density $\mu_0$, we find:
$$\label{eqmu0}
|| (P^t)^n\mu_0 - \mu_\text{stat}|| \propto (\lambda(P))^n.$$
According to Eqs. (\[eqdn\]) and (\[eq:mix1\]), $\lambda(P)^{t(\epsilon)} \propto \epsilon$, i.e. $\lambda(P) \propto \epsilon^{1/t(\epsilon)}$. Hence, the smaller $\lambda(P)$ the shorter the mixing time (Fig. \[... | 897 | 1,015 | 1,569 | 954 | 2,622 | 0.778349 | github_plus_top10pct_by_avg |
a}-G_{ac}\frac{1}{1+i\lambda_T G_{cc}}i\lambda_T G_{ca}\,,$$ where $G_{nm}=W^\dag_n G W_m$ and $\lambda_T$ is the coupling constant of the “terminator,” $$\label{eq:s08}
\lambda_T=\frac{1-r}{1+r}=\tanh\frac{\alpha+i\phi}{2}\,.$$
Equation (\[eq:s06\]) has the same form as Eq. (\[eq:s05\]), but for the measuring ant... | 898 | 3,249 | 1,799 | 934 | 2,079 | 0.782958 | github_plus_top10pct_by_avg |
Mills theory [@Litim:1998nf; @Pawlowski:2005xe] in Polyakov gauge, $$\begin{aligned}
\nonumber
\hspace{-.5cm} \partial_t \Gamma_{k}& =
& \frac{\beta}{2}
\int \0{d^3 p}{(2 \pi)^3} \left(\frac{1}{\Gamma_k^{(2)}
+ R_A}\right)_{00}\partial_t R_{0,k}\\
& & +
\frac{T}{2} \sum_{n\in \Z}
\int \0{d^3 p}{(2 ... | 899 | 2,441 | 1,247 | 836 | 2,353 | 0.780628 | github_plus_top10pct_by_avg |
erational profile (of collection $Z$) is $$P(Z) = \lim_{\;k \to \infty} \frac{N_Z(\{{\mathit{s}}_n\}, k)}{k}.$$
### Conversion into a rate {#S:ABSOLUTE_OP_PROFILE_RATE}
Section \[S:INTRO\_REACTIVE\] mentions the synchronization function, a cross-reference between discrete and real time. During each step, an amount of... | 900 | 2,906 | 2,481 | 978 | 1,333 | 0.79083 | github_plus_top10pct_by_avg |
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