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
N}}$. The following construction generalizes the Poincaré-Birkhoff-Witt basis of quantized enveloping algebras given by Lusztig. Let $i_1,i_2,\dots ,i_n\in I$ such that $\ell (1_{\chi }{\sigma }_{i_1}{\sigma }_{i_2}\cdots {\sigma }_{i_n})=n$. For all $\nu \in \{1,2,\dots,n\}$ let $$\begin{gathered} \label{eq:betak} ...
1,201
1,485
986
1,179
null
null
github_plus_top10pct_by_avg
x{\boldmath$\psi$}$ and $\mbox{\boldmath$\phi$}$ can be used as the weight for sampling the coordinates $X$ entering the classical integral in Eq. (\[eq:sigma-sb\]). Then, for each initial value $X$, Eqs. (\[eq:matrixSigma\]) must be integrated in time so that averages can be calculated. It is worth to note that in suc...
1,202
313
2,074
1,243
null
null
github_plus_top10pct_by_avg
sidering the effect of the angular momentum. If the accretion disc is spatially resolved, we expect further mass loss happens due to, e.g., the disc winds [e.g., @Blandford:1999aa; @Zahra-Zeraatgari:2016aa; @Begelman:2016aa] and/or jets from a close vicinity of the BH [e.g., @Ohsuga:2005aa; @Jiang:2014aa; @Yuan:2015aa...
1,203
1,884
2,612
1,327
null
null
github_plus_top10pct_by_avg
beta} \left\{ \sum_{i = 1}^{n} L(r_{i}(\beta)) \right\}. \end{aligned}$$ The case of $L(r_{i}(\beta)) = r_{i}(\beta)^{2}$ is well-known (see, e.g., Refs. [@doi:10.1111/j.1751-5823.1998.tb00406.x], [@legendre1805nouvelles], and [@stigler1981]). In the case of an asymmetric loss function, we refer the reader to, e.g., Re...
1,204
5,034
979
658
754
0.800756
github_plus_top10pct_by_avg
t,0){\right\rangle}_{L^2(G\times S)} + {\left\langle}\psi(\cdot,\cdot,E_m),v(\cdot,\cdot,E_m){\right\rangle}_{L^2(G\times S)}.\end{aligned}$$ The elements of $H_1$ are of the form $\tilde\psi=(\psi,q,p_0,p_m)\in L^2(G\times S\times I)\times T^2(\Gamma)\times L^2(G\times S)^2$. More precisely, the elements of $H_1$ are...
1,205
660
1,108
1,201
null
null
github_plus_top10pct_by_avg
s (g(N^{n-2k}) \cap (U_P))$ by $N^{n-2k}_{int}$, and the complement $N^{n-2k} \setminus N^{n-2k}_{int}$ by $N^{n-2k}_{ext}$. The manifolds $N^{n-2k}_{ext}$, $N^{n-2k}_{int}$ are submanifolds in $N^{n-2k}$ of codimension 0 with the common boundary, this boundary is denoted by $N_Q^{n-2k-1}$. The self-intersection manifo...
1,206
443
1,617
1,228
2,675
0.777931
github_plus_top10pct_by_avg
akli], with the result [@li] that they are effectively proportional to the coupling $g_{37}^2$ in (\[coupl-N\]). The amplitudes depend on kinematical invariants expressible in terms of the Mandelstam variables: $s=-(k_1 + k_2)^2$, $t=-(k_2 + k_3)^2$ and $u=-(k_1 + k_3)^2$, which satisfy $s + t + u =0$ for massless part...
1,207
2,382
1,497
1,169
null
null
github_plus_top10pct_by_avg
a_\varphi$ is the largest relevant solution of the eigenvalue equation $$\label{csawlamdafi} \mbox{det}\left| \left({\partial X^{(r+1)}_i\over \partial X^{(r)}_j} \right)^{*}- \lambda_\varphi\,\delta_{ij} \right|=0\>,$$ where the asterisk means that the derivatives should be taken at the tricritic...
1,208
1,138
1,964
1,234
null
null
github_plus_top10pct_by_avg
+2b} z_j^{\ast} \end{pmatrix} &0 \\ 0& 0 &id \end{pmatrix}.$$ Here, the $(2,2)$-block of the above formal matrix corresponds to $B(-2be_1+e_2)\oplus$ $B(-ae_1+e_3)\oplus$ $B(e_2+e_3)$ with the Gram matrix $A(2b(2b-1), a(a+1), a(2b-1))\oplus (a+2b)$ and $id$ in the $(1,1)$-block corresponds to the direct summand $(\...
1,209
1,964
1,484
1,160
2,643
0.778197
github_plus_top10pct_by_avg
obi symbol properties ------------------------ The Jacobi symbol $(a | b)$ is defined for $b$ odd and positive, and arbitrary $a$. We work primarily with non-negative $a$, and make use of the following properties of the Jacobi symbol. Assume that $a$ is positive and that $b$ is odd and positive. Then (i) \[it:zero\]...
1,210
5,821
587
590
2,748
0.777304
github_plus_top10pct_by_avg
m_j}\mathcal{F}_{_{j-2l}}(\tilde{m})$ is naturally identified with $\sum_{0\leq l \leq m_j}\mathcal{F}_{_{j-2l}}(m)$. As for Equation (\[ea20\]) of Step (1), we need to express $\sum_{0\leq l \leq m_j}\mathcal{F}_{_{j-2l}}(m)$ precisely. Each entry $\tilde{x}_i$ of $(\tilde{m_{i,j}}, \tilde{s_i} \cdots \tilde{w_i}...
1,211
4,661
329
878
null
null
github_plus_top10pct_by_avg
\end{aligned}$$ and for the bundle ${\cal E}$, $$c_1^{\rm rep}({\cal E})|_{\alpha} \: = \: \sum_a \frac{n_a}{k} J \alpha^{-n_a} \: - \: \frac{m}{k} J \alpha^{-m},$$ $$\begin{aligned} {\rm ch}_2^{\rm rep}({\cal E})|_{\alpha} & = & {\rm ch}_2^{\rm rep}( \oplus_a {\cal O}(n_a) )|_{\alpha} \: - \: {\rm ch}_2^{\rm rep}( {\c...
1,212
985
1,660
1,167
null
null
github_plus_top10pct_by_avg
1273.001){#fig1} ![Anterior segment OCT showing corneal thickness maps of both eyes. The right cornea graft has a minimal thickness of 579 *μ*m versus 237 *μ*m in the left eye with Brittle Cornea.](CRIOPM2020-4381273.002){#fig2} ![Demonstration of cataract and inferior posterior synechiae of the right eye. The cornea...
1,213
629
1,197
1,613
null
null
github_plus_top10pct_by_avg
\le x_2$, $y_1 \le y \le y_2$, and $z_1 \le z \le z_2$ in a Cartesian grid. In a cylindrical grid, we consider a rectangular torus with density $\rho=1$, occupying the regions with $R_1 \le R \le R_2$, $\phi_1 \le \phi \le \phi_2$, and $z_1 \le z \le z_2$. Table \[tb:convergence\_test\] lists the parameters of the soli...
1,214
1,824
2,638
1,477
3,245
0.77379
github_plus_top10pct_by_avg
ptions, and , the integrals $\int_{S\times I}\sigma_{jk}(x,\omega',\omega,E',E)d\omega' dE'$ (resp. $\int_{S\times I}\sigma_{jk}(x,\omega,\omega',E,E')d\omega' dE'$) over $S\times I$ are to be replaced with $\int_S\tilde\sigma_{kj}(x,\omega',\omega,E)d\omega'$ (resp. $\int_{S}\sigma_{jk}(x,\omega,\omega',E)d\omega'$) o...
1,215
202
1,236
1,310
3,106
0.774856
github_plus_top10pct_by_avg
$q^{\frac{1}{2}(n^2-\sum_i\lambda_i^2)}R_{\mathfrak{l}_\lambda}^\mathfrak{g}(1)$ is a character of $(\mathfrak{g},+)$. \[charab\] Absolutely indecomposable representations ========================================= Generalities on quiver representations {#genquiv} -------------------------------------- Let $\Gamma$...
1,216
998
1,127
1,163
3,949
0.769058
github_plus_top10pct_by_avg
e on-shell physical states defined by these asymptotic string fields, and thus the physical S-matrix. Thus the supersymmetry algebra is realized on the physical S-matrix, and we can identify the transformation (\[complete transformation\]) with space-time supersymmetry. Extra unphysical symmetries {#extra symm} ------...
1,217
361
1,376
1,253
null
null
github_plus_top10pct_by_avg
estimator =================== In this section we obtain the asymptotic size of the uniform deviation of the ideal estimator (\[ideal0\]) from the density $f$, that is, we will consider the a.s. asymptotic size of $$\sup_{t\in D_r} |\bar f(t;h_n)-f(t)|:=\|\bar f(t;h_n)-f(t)\|_{D_r}$$ As usual this quantity is divided ...
1,218
544
1,006
1,187
2,773
0.777065
github_plus_top10pct_by_avg
ance which is equal to a lattice constant (red bonds, weighted with $v$). On the other hand, in the case of CSAWs model (b), the polymers $P_3$ and $P_2$ are cross-linked at the two sites, so that each contact contributes the weight factor $w$, while the red bonds (marked by $t$) correspond to the interactions between ...
1,219
1,305
2,022
1,391
null
null
github_plus_top10pct_by_avg
al dimension of such operators as a function of the two parameters $(k,f)$ of the supergroup sigma-model. At the WZW point these operators are descendants in the highest-weight representations of the left affine Lie algebra. Operators of the form $:j_L \phi :$ {#operators-of-the-form-j_l-phi .unnumbered} -------------...
1,220
461
1,087
1,138
null
null
github_plus_top10pct_by_avg
size specified by plot title. For each baseline SGD run, we have a corresponding large-noise SGD run, denoted by $\diamond$ with the same color. As mentioned, these $\diamond$ runs are designed to match the noise covariance of SGD with larger step size or smaller batch size. In addition to $\times$ and $\diamond$, we a...
1,221
699
468
1,209
null
null
github_plus_top10pct_by_avg
.54 92.71  36 months 47.71 81.45 68.13 79.76 66.71 84.34 62.36 77.73 66.18 73.17   *p* \<0.01 0.34 0.86 0.60 0.15 Adjusted for i...
1,222
19
2,031
1,387
null
null
github_plus_top10pct_by_avg
that, by this definition, $r_i$ for $i\ge1$ equals $((d-2)\wedge(i+3))-{\epsilon}$ and increases until it reaches $d-2-{\epsilon}$. We prove below by induction that $\sum_x|x|^{r_i}|\Pi(x)|$ is finite for all $i\ge0$. This is sufficient for the finiteness of $\sum_x|x|^{{\scriptscriptstyle}\frac{d+2}3}|\Pi(x)|$, since ...
1,223
347
369
1,333
1,146
0.79358
github_plus_top10pct_by_avg
_{i,i}')a_i(\pi m_{i,i}')$ since its nondiagonal entries contain $\pi^2$ as a factor and its diagonal entries contain $\pi^4$ as a factor. Thus the above equation equals $$a_i'=a_i+\sigma(\pi)\cdot {}^tm_{i,i}'a_i+ \pi\cdot a_i m_{i,i}'.$$ By letting $a_i'=a_i$, we have the following equation $$\sigma(\pi)\cdot {}^tm_{...
1,224
1,613
1,320
1,166
null
null
github_plus_top10pct_by_avg
1,j} \right) \ = \ \operatorname{{\textsf}{ogr}}B_{ij}.$$ \(3) When $k=0$, the assertion $eJ^k\delta^{k} = \operatorname{{\textsf}{ogr}}N(k)$ is just the statement that $e{{\mathbb{C}}[{\mathfrak{h}}\oplus {\mathfrak{h}}^*]}= e({{\mathbb{C}}[{\mathfrak{h}}\oplus {\mathfrak{h}}^*]}\ast {{W}}) $. When $k>0$, part (i) a...
1,225
1,283
1,403
1,188
null
null
github_plus_top10pct_by_avg
ss Type 0 __text 00000043 0000000100000f30 TEXT [...] You can also do the same trick to get the size of whole segments (as opposed to sections) by using the syntax segment$start$__TEXT / segment$end$__TEXT. Q: Why does new allocate 1040 extra bytes the first time? I was creating this simple te...
1,226
6,794
86
388
11
0.841901
github_plus_top10pct_by_avg
80 (25.5)   1.26 (0.86, 1.85) A allele 88 (27.8) 16 (21.6)   1.40 (0.76, 2.56) G allele 151 (70.0) 234 (74.5) 0.2416 1 G allele 228 (72.2) 58 (78.4) 0.2756 1 **rs6603797** **rs6603797**   ...
1,227
2,069
1,368
1,299
null
null
github_plus_top10pct_by_avg
potent group, and suppose that $A\subset G$ is a finite $K$-approximate group. Then there exist a subgroup $H\subset A^{K^{e^{O(s)}}}$ normalised by $A$ and a nilprogression $P_{\text{\textup{nil}}}(x;L)$ of rank at most $e^{O(s^2)}K\log^{O(s)}2K$ such that $$A\subset HP_{\text{\textup{nil}}}(x;L)\subset H\overline P(x...
1,228
260
1,136
1,202
2,427
0.779834
github_plus_top10pct_by_avg
s is highly relevant for geometric complexity theory, since it was recently shown in [@kumar10b] and [@burgisserikenmeyer11] that the studied varieties (the orbit closures of the determinant and permanent on the one hand, and of the matrix multiplication tensor and the unit tensor on the other hand) are in fact never n...
1,229
1,659
1,101
1,126
null
null
github_plus_top10pct_by_avg
 \[fig2\] and Fig. \[fig3\], Fig. \[fig4\] depicts the mean momentum $p(t)$ of the atoms for two different values of the occupation number $\bar{n}=N/L$ (number of atoms per lattice cite) – $\bar{n}=1$ (upper panel) and $\bar{n}=2/7$ (lower panel). As to be expected, the dynamics of the system depends on the value of $...
1,230
445
878
1,324
2,810
0.77681
github_plus_top10pct_by_avg
times of measurement to record random variations in detected x-ray intensity are acquired. However, in this work, the collected datasets are not supported by the aforementioned factors and they fall outside the scope of this paper. The results presented here are focusing on the implementation of a new algorithm to lim...
1,231
4,280
1,577
1,073
null
null
github_plus_top10pct_by_avg
y order in a semi-classical expansion. We will show that the knowledge of the poles in these OPEs is enough to fix all the subleading terms. The idea driving the bootstrap is to ask for the compatibility of the elementary OPEs with both current conservation and the Maurer-Cartan equation. Current-current OPEs {#curren...
1,232
69
1,883
1,366
3,101
0.774883
github_plus_top10pct_by_avg
nd the periodicity of the KK circle at infinity $\chi\sim\chi+L$ will be determined by smoothness of the metric at $\rho=\rho_0$. We now add electric 3-form flux to the bubbles, $C=\frac{Q_0}{2\pi^2}(\star \epsilon_3)$, where $\epsilon_3$ is the volume element of the spatial $S^3$. Concretely, the field strength is $$...
1,233
751
1,971
1,419
3,583
0.77139
github_plus_top10pct_by_avg
u_i&1+\pi w_i \end{pmatrix}\in \mathrm{GL}_{n_i}(B\otimes_AR),$$ where $s_i$ is an $(n_i-2) \times (n_i-2)-$matrix, etc.\ 3. Let $i=2m$ be even. Then $g$ stabilizes $Z_i$ and induces the identity on $W_i/(X_i\cap Z_i)$. For the proof, it is easy to show that $g$ stabilizes $Z_i$. To prove the latter, we choose an ele...
1,234
2,510
1,421
1,176
1,617
0.787545
github_plus_top10pct_by_avg
u i}_\alpha(u) \right)}$ are $m\times q$ matrix functions of $u$ and we denote the partial derivatives by $u^\alpha_i={\partial}u^\alpha/{\partial}x^i$. The matrix $L_i^\alpha$ satisfying the conditions[@Burnat:1972] \[eq:intelem\] u\_i\^[{ L\_i\^:\_\^[i]{}L\_i\^=0, =1,…,q }]{} at some open given point $u_0\in U$ is ...
1,235
2,446
2,801
1,320
null
null
github_plus_top10pct_by_avg
d B.-J. Schaefer for discussions. We thank O. Jahn for discussions and collaboration at an early state of this project. FM acknowledges financial support from the state of Baden-Württemberg and the Heidelberg Graduate School of Fundamental Physics. Faddeev-Popov determinant {#app:FPdet} ========================= From...
1,236
4,893
208
834
null
null
github_plus_top10pct_by_avg
ssion. The application of an integer constructor labels the free variable as an integer variable. An integer condition, e.g. $\geq/2$, is applicable if both arguments are integer expressions. Since integer variables denote unknown integers, integer expressions are allowed to contain integer variables. Applications of i...
1,237
6,138
1,098
740
253
0.815848
github_plus_top10pct_by_avg
}_{1}}+{{\theta}_{2}}), \\ & {{J}_{12}}=-{{L}_{1}}\cos {{\theta}_{1}}-{{L}_{2}}\cos ({{\theta}_{1}}+{{\theta}_{2}}), \\ & {{J}_{13}}={{J}_{14}}=0, \\ & {{J}_{21}}=-{{L}_{2}}\sin ({{\theta}_{1}}+{{\theta}_{2}}), \\ & {{J}_{22}}=-{{L}_{2}}\cos ({{\theta}_{1}}+{{\theta}_{2}}), \\ & {{J}_{23}}={{J}_{...
1,238
2,630
2,096
1,402
null
null
github_plus_top10pct_by_avg
{\ast}=\underline{M}$. As a matrix, each element of $\underline{M}^{\ast}(R)$ for a flat $A$-algebra $R$ can be written as $\begin{pmatrix} 1+2 z \end{pmatrix}$. We define another functor from the category of commutative flat $A$-algebras to the category of sets as follows. For any commutative flat $A$-algebra $R$, le...
1,239
619
1,035
1,249
null
null
github_plus_top10pct_by_avg
imal categories in the Pascal VOC Part dataset. For the ILSVRC 2013 DET Animal-Part dataset and the CUB200-2011 dataset, we learned an AOG for the head part[^3] of each category. It is because all categories in the two datasets contain the head part. We did not train human annotators. Shape differences between two part...
1,240
654
272
1,017
1,027
0.795439
github_plus_top10pct_by_avg
phic to $\PP^2_w$ and the isomorphism is induced by the branched covering $$\label{covering} \PP^2\ni [X_0:X_1:X_2] \overset{\phi}{\longmapsto} [X_0^{w_0}:X_1^{w_1}:X_2^{w_2}]_w \in\PP^2_w.$$ Note that this branched covering is unramified over $$\PP^2_{w} \setminus \{ [X_0,X_1,X_2]_{w} \mid X_0\cdot X_1\cdot X_2 =...
1,241
384
785
1,295
null
null
github_plus_top10pct_by_avg
\[r31\]. Thus $\tilde{T}$ is an element of $\underline{M}_j^{\ast}(R)$, where $\underline{M}_j^{\ast}$ is the group scheme in Section \[m\] associated to $M_0^{\prime}\oplus C(L^j)$ so that $\underline{G}_j'$ is defined as the closed subgroup scheme of $\underline{M}_j^{\ast}$ stabilizing the hermitian form on $M_0^{\...
1,242
1,165
1,270
1,219
2,122
0.782583
github_plus_top10pct_by_avg
\hat{b}^{il}_{-} ( u - \frac{1}{2} (k+l) \hbar ) - \sum_{l=i+2}^{N} \hat{b}^{i+1,l}_{-} ( u- \frac{1}{2} (k+l-1) \hbar) \right): \nonumber\\ & & ~~~~- :\mbox{exp} \left( (b+c)^{i,i+1} ( u + \frac{1}{2} (k+i) \hbar ) \right) \nonumber\\ & & ~~~~~~~~\times \mbox{exp} \left( \hat{a}^i_+ (u) + \sum_{l=i+1}^N \hat{b}^{il}_...
1,243
1,383
983
1,208
null
null
github_plus_top10pct_by_avg
=3$ system, i.e., equation (\[eq:Bog\]). Other systems with similar behaviour have been presented in [@BW]. Acknowledgements {#acknowledgements .unnumbered} ---------------- PX acknowledges support from the EPSRC grant [*Structure of partial difference equations with continuous symmetries and conservation laws*]{}, E...
1,244
50
2,211
1,437
2,455
0.779594
github_plus_top10pct_by_avg
P51884 Lumican 26.62 35.50 38.4 6.61 P01876 Immunoglobulin heavy constant alpha 1 25.67 29.18 37.6 6.51 Q08380 Galectin-3-binding protein 25.15 17.78 65.3 5.27 P67936 Tropomyo...
1,245
4,474
659
767
null
null
github_plus_top10pct_by_avg
a trial‐specific adjustment term for the baseline outcome value (here, centered at the mean for each trial ( ${\bar{Y}}_{\mathit{Bi}}$) to aid interpretation of the trial‐specific intercepts). For example, when there are *K* = 10 trials, there would be 10 *β* ~*i*~ terms and 10 *λ* ~*i*~ terms. Of main interest is an ...
1,246
766
2,329
1,231
344
0.812502
github_plus_top10pct_by_avg
+ \int_0^t -\nabla U(w_0) ds + \int_0^t \cm \lrp{I - 2\gamma_s \gamma_s^t} dV_s + \int_0^T N(x_s) dW_s \end{aligned}$$ Where $\gamma_t := \frac{x_t - y_t}{\|x_t-y_t\|_2} \cdot \ind{\|x_t-y_t\|_2 \in [2\epsilon, \Rq)}$. The coupling $(x_t,y_t)$ defined in and is identical to the coupling in (with ...
1,247
1,977
1,354
1,199
3,892
0.769479
github_plus_top10pct_by_avg
cO_{X}(D))$ is isomorphic to $\CC[x,y,z]_{w,d}$, the $w$-homogeneous polynomials of degree $d := \deg_w({\left \lfloor D \right \rfloor})$. It is a well-known result for integral Weil divisors. The general rational case follows from the fact that by definition $\cO_X(D) = \cO_X({\left \lfloor D \right \rfloor})$. The ...
1,248
980
1,221
1,158
2,709
0.777697
github_plus_top10pct_by_avg
36 (32.7) 40 (27.0)   1.31 (0.77, 2.25) A allele 43 (28.7) 6 (23.1)   1.34 (0.50, 3.56) G allele 74 (67.3) 108 (73.0) 0.3206 1 G allele 107 (71.3) 20 (76.9) 0.5572 1 **rs6603797** **r...
1,249
4,800
308
669
null
null
github_plus_top10pct_by_avg
r to the literature for general results. We begin by fixing a field $\bbf$; all our modules will be modules for the group algebra $\bbf{\mathfrak{S}_}n$. We assume familiarity with James’s book [@j2]; in particular, we refer the reader there for the definitions of partitions, the dominance order, the permutation modul...
1,250
982
1,031
1,207
1,657
0.787113
github_plus_top10pct_by_avg
on_{\star}=-2/mr_{\star}^2$. After resonance when $\delta' \to +\infty$, the CI bound state energy behaves as $\epsilon_b'\simeq -1/ma^2$, which translates into $\epsilon_b'/\epsilon_{\star}'\simeq (\delta'+A)^2/2\simeq \delta^{'2}/2$ in terms of the parameter $\delta'$ introduced above. Similarly, in the BFRM, the bou...
1,251
417
1,277
1,331
null
null
github_plus_top10pct_by_avg
any solution $\phi\in {\mathcal{H}}_P(G\times S\times I^\circ)$ of the problem , , that further satisfies \[asscl\] \_[|\_+]{}T\^2(\_+)(,,0)L\^2(GS), is unique and obeys the estimate \[csda40aa\] \_[[H\_1]{}]{} (\_[L\^2(GSI)]{}+\_[T\^2(\_-)]{}), where $c'$ is given in . The proof is based on “variations” and it is qu...
1,252
528
1,763
1,319
null
null
github_plus_top10pct_by_avg
k$ vertices, there are at most $\binom{k}{2}$ edges whose addition may produce a cycle. [This includes edges already present in the component, as an edge with multiplicity 2 (double edge) forms a 2-cycle.]{} Thus, the $p$ edges can be chosen in $\binom{k}{2}^p<k^{2p}$ ways. Let $\{e_1,e_2,\ldots, e_p\}$ denote a set of...
1,253
1,423
1,281
1,213
2,961
0.775804
github_plus_top10pct_by_avg
s. Here's the code. int main (void) { const char *alp = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"; char *ptr = &alp[3]; printf("%s\n", ptr); return 0; } Edit- Sorry for not mentioning the errors. The thing is I get tons of different errors depending on where I put different asterisks and ampersands. There is...
1,254
6,702
225
196
42
0.832662
github_plus_top10pct_by_avg
. \[thm:DefDiVar\] Let $D\in{\mathrm{Di}}{\mathrm{Alg}}0$. Then the following conditions are equivalent: 1. $D\in{\mathrm{Di}}{\mathrm{Var}}$ 2. $\widehat D=\bar D\oplus D\in{\mathrm{Var}}$ the definition in the sense of Eilenberg 3. $D\vDash \Psi^{x_i}_{\mathrm{Alg}}\,f$ for every $f\in T_0({\mathrm{Var}})$, $\...
1,255
1,290
1,085
1,190
2,469
0.779498
github_plus_top10pct_by_avg
e cannot be sure that system (\[eq:SW:15\]) for $f(r)$ is well-defined in the sense that it represents a system for $f(r)$ express in terms of $r$ only. To ensure this, we begin by introducing vector fields orthogonal to the wave vector $\lambda$, that is, vector fields of the form \[eq:SW:16\] X\_a=\^i\_a(u)\_[x\^i]{...
1,256
2,200
2,909
1,352
null
null
github_plus_top10pct_by_avg
t $D^{(k)} = (d_{ij}^{(k)}-\delta_{i,1}\cdot \delta_{kj})_{i,j=1,\dots,n}$. Expressing $\lambda$ as linear combination of the dual basis then leads to the system of linear equations $D^{(k)} x = 0$ $(k=1,...,n)$. As pointed out by Mariano it has a unique solution (up to scalars). Again, this is no closed formula, but ...
1,257
929
309
632
909
0.797879
github_plus_top10pct_by_avg
$, one has $\bar{a}\bar{b} = [a+F^{n-1}R][b+F^{m-1}R] \subseteq [ab+F^{n+m-1}R]$. Since $\bar{a}\bar{b}\not=0$, $ab\in F^{n+m}R\smallsetminus F^{n+m-1}R$, whence $\bar{a}\bar{b}=\sigma(ab)$ is the image of $ab$ in $\operatorname{gr}_F(AB)$. \(2) Define a map $\rho: \operatorname{gr}_FA\times \operatorname{gr}_FB \to \...
1,258
2,177
1,131
1,173
null
null
github_plus_top10pct_by_avg
restate and prove Theorem \[bicirc\]. \[bicirctech\] There is a function $f_{\ref{bicirctech}}\colon \bZ \to \bZ$ so that, for every integer $s \ge 2$, if $M$ is a matroid without a $U_{s,2s}$-minor and with a $B^+(K_{r(M)})$-restriction framed by $B$, then there is a set $\wh{B} \subseteq B$ and a $\wh{B}$-clique $\w...
1,259
494
537
1,192
3,154
0.77444
github_plus_top10pct_by_avg
ring sites *wR*(*F*^2^) = 0.089 H-atom parameters constrained *S* = 1.14 *w* = 1/\[σ^2^(*F*~o~^2^) + (0.0341*P*)^2^ + 13.8363*P*\] where *P* = (*F*~o~^2^ + 2*F*~c~^2^)/3 19520 reflections (Δ/σ)~max~ = 0.009 950 parameters Δρ~...
1,260
134
1,436
1,536
null
null
github_plus_top10pct_by_avg
required to be large enough, but still independent of the mesh size $h$, in order to guarantee the well-posedness of the discontinuous Galerkin formulation. Details will be given later. It is clear that the exact solution $u$ to Equation (\[eq:ellipticeq\]) satisfies $$\label{eq:dg-exactsol} A(u,v) = (f,v)\qquad\text...
1,261
729
786
1,303
null
null
github_plus_top10pct_by_avg
t \int_{S\times I}\sigma(\cdot,\omega',\cdot,E',\cdot)d\omega' dE'\right\Vert}_{L^\infty(G\times S\times I)}={\mathop{\mathrm{ess\hspace{1mm}sup}}}_{(x,\omega,E)\in G\times S\times I}\int_{S\times I}\sigma(x,\omega',\omega,E',E)d\omega' dE', \nonumber\\ & {\left\Vert \int_{S\times I}\sigma(\cdot,\cdot,\omega',\cdot,E')...
1,262
135
2,005
1,393
null
null
github_plus_top10pct_by_avg
\bar{b}_{ki}-f_j\bar{h}_i=0 \label{nobraneE84} \\ & \bar{g}_{ki}\bar{b}_{jj}-\bar{f}_ib_{ij}-\bar{g}_{jj}\bar{b}_{ki}+g_{ij}\bar{h}_i=0 \nonumber \\ & -g_{ji}b_{kj}+\bar{g}_{ii}h_j+g_{kj}b_{ji}-f_j\bar{b}_{ii}=0 \nonumber \\ & g_{ji}\bar{b}_{jj}-\bar{g}_{ii}b_{ij}-\bar{g}_{jj}b_{ji}+g_{ij}\bar{b}_{ii}=0 \quad .\nonumbe...
1,263
927
1,537
1,293
null
null
github_plus_top10pct_by_avg
finition \[D:DISJOINT\_ENSEMBLES\], disjointness entails that ${{\operatorname{dom}{\Psi}}}\thickspace\cap\thickspace{{\operatorname{dom}{\Phi}}} = \varnothing$. Thus, if $i \in {{\operatorname{dom}{\Upsilon}}}$, exactly one of two cases hold: either A: $i \in {{\operatorname{dom}{\Psi}}}$ and $i \notin {{\operatorname...
1,264
534
1,816
1,259
null
null
github_plus_top10pct_by_avg
Big(\PP^2_w, \mathcal{O}_{\PP^2_w}\left( kH+K_{\PP^2_w} - \mathcal{C}^{(k)} \right)\Big) = \chi \left( \PP^2_w,\mathcal{O}_{\PP^2_w} \left( kH+K_{\PP^2_w} - \mathcal{C}^{(k)} \right) \right) \\ & =1 + \frac{1}{2} \left( kH+K_{\PP^2_w} - \mathcal{C}^{(k)} \right) \cdot \left( kH - \mathcal{C}^{(k)} \right) + R_{\PP^2_w}...
1,265
500
1,440
1,245
null
null
github_plus_top10pct_by_avg
\begin{aligned} \hat{u}_{ {\bf k} }(\tau) &=& \hat{a}_{{\bf k} } f(k,\tau)+ \hat{a}_{-{\bf k} }^{\dagger} f^{*}(k,\tau), \label{sol11} \\ \hat{\pi}_{{\bf k} }(\tau) &=& \hat{a}_{{\bf k} } g(k,\tau)+ \hat{a}_{-{\bf k} }^{\dagger} g^{*}(k,\tau). \label{sol22}\end{aligned}$$ where $f(k,\tau)'=g(k,\tau)$. When we ...
1,266
3,959
1,449
895
null
null
github_plus_top10pct_by_avg
ion parameters. Similarly to what we did in , we derive two approximate confidence sets: one is an $L_\infty$ ball and the other is a hyper-rectangle whose $j^{\mathrm{th}}$ side length is proportional to the standard deviation of the $j^{\mathrm{th}}$ coordinate of $\hat{\gamma}_{{\widehat{S}}}$. Both sets are center...
1,267
2,821
1,549
1,214
null
null
github_plus_top10pct_by_avg
ion $\varphi^a=G_{ret}^{ab}q_{c}F^c_b$ we get \^a\^bG\_s\^[ab]{}=G\_[ret]{}\^[ac]{}F\^d\_cG\_[ret]{}\^[be]{}F\^f\_eQ\_[df]{}=G\_[ret]{}\^[ac]{}G\_[ret]{}\^[be]{}N\_[ce]{} \[ne21\] From effective actions to Langevin equations --------------------------------------------- Let us now investigate a scalar field theory ...
1,268
367
2,263
1,284
null
null
github_plus_top10pct_by_avg
LB($n^{0.8}$) 0.000 0.002 0.002 0.000 0.002 0.000 0.000 SDB($n^{0.6}$) 0.000 0.000 0.000 0.000 0.000 0.000 0.000 SDB($n^{0.8}$) 0.000 0.000 0.000 0.000 0.000 ...
1,269
5,338
258
752
null
null
github_plus_top10pct_by_avg
make the following approximation: - When assimilating a non-baseline observation, ${\bar{\mathcal{A}}}$ is kept fixed at its previous value, and for updating ${\mathcal{A}}$ it is assumed that ${\bar{\nu}}^{-1}=0$. Approximation B2 implies that for ${\mathbf{x}}_t\neq{\mathbf{0}}$, $$\begin{aligned} Y_t|~ {\bar{...
1,270
2,913
1,708
1,206
null
null
github_plus_top10pct_by_avg
, where $\sigma_n$ is the time it takes for the walk-on-spheres to exit the $n$th sphere. Thus $\sum_{n=0}^{N-1} r_n^{\alpha}\, V_{1}(0, {f}(\rho_n + r_n\cdot))\leq\kappa \sum_{n=0}^{N-1} \sigma_n = \kappa\,\sigma_D$. We thus have that $$\mathbb{E}_x\left[\left( \sum_{n=0}^{N-1} r_n^{\alpha}\, V_{1}(0, {f}(\rho_n + r_...
1,271
963
1,183
1,200
3,682
0.770724
github_plus_top10pct_by_avg
$$ The Poincaré series of $N(k)$ is now easy to compute. First, in the [*canonical grading*]{}, shows that $$p(\Delta_d(\mu), v, W) = v^{D(d,\mu)}\frac{\sum_{\lambda} f_{\lambda}(v) [\lambda\otimes \mu]}{\prod_{i=2}^n(1-v^i)} \qquad\mathrm{and\ so}\qquad p(e\Delta_d(\mu), v)= v^{D(d,\mu)} \frac{f_{\mu}(v)}{\prod_{i=...
1,272
1,206
1,336
1,198
4,064
0.768366
github_plus_top10pct_by_avg
ivalence relations $R$ on $X={{\mathbb A}}^2$ (in any characteristic) such that the geometric quotient $X/R$ exists yet $R$ is strictly smaller than the fiber product $X\times_{X/R}X$. Closely related examples are in [@venken; @philippe]. In characteristic zero, this leaves open the following: \[sch.th.quot.quest\] L...
1,273
2,373
1,929
1,230
1,328
0.790923
github_plus_top10pct_by_avg
I have no idea how to read what address is currently stored in whatever OpenGL has currently bound as the vertex attrib array, so I cannot test whether or not it is pointing to the vertex data. I'm pretty sure that it's pointing to address 0 for some reason though. Edit: It turns out it was not the hard-coded 0 that w...
1,274
4,233
412
1,195
676
0.802583
github_plus_top10pct_by_avg
rmation up to an additive term. $$\label{transform} G_2 \left( \frac{a\tau +b}{c\tau +d}\right) = (c\tau +d)^2 G_2 (\tau) - \frac{c}{4\pi i} (c\tau +d).$$ The ring $\Q [G_2,\ G_4,\ G_6]$ is called the ring of *quasi-modular* forms (see [@kaneko-zagier]). We have $$1+\sum_{n\geq 1}\H_{(n-1,1)}\left(e^{u/2},e^{-u...
1,275
3,715
1,769
1,082
2,887
0.776306
github_plus_top10pct_by_avg
entity \otimes \identity + p(\mathbf{P})]\enspace.\end{aligned}$$ The solution is $$\label{superop-soln} S_t = \exp\left([i(\identity \otimes H - H \otimes \identity) - p \identity \otimes \identity + p(\mathbf{P})]t\right)\enspace.$$ We now define the decoherence operator $\mathbf P$. This operator will corresp...
1,276
2,948
1,530
1,174
3,655
0.770882
github_plus_top10pct_by_avg
ary morphisms since all morphisms preserve left Kan extensions along left adjoint functors (see [@groth:can-can Prop. 5.7] and [@groth:can-can Rmk. 6.11]). As for the second statement, there is an adjoint triple $0\dashv\pi_{[1]}\dashv 1$ and hence an induced adjoint triple $1^\ast\dashv \pi_{[1]}^\ast\dashv 0^\ast$. T...
1,277
608
1,101
1,247
1,988
0.78379
github_plus_top10pct_by_avg
f({\mathbf x}) &\sim {\GP \left(m({\mathbf x}),\,\, k({\mathbf x},{\mathbf x}') \right)}, \\ y_i &= \mathcal{H}_{{\mathbf x},i} f({\mathbf x})+\varepsilon_i. \end{aligned}$$ As discussed, for example, in [@Sarkka:2011; @SolinSarkka2015] the GP regression equations can be extended to this kind of mode...
1,278
2,003
1,335
1,267
3,495
0.771947
github_plus_top10pct_by_avg
------------------------------------------------------ The zeroth and first order $\hat{S}$ matrix elements can be calculated as follows: $$\begin{aligned} \hat{S}_{ii}^{(0+1)} &=& \left( e^{-i \hat{H}_{0} x} \right)_{i k} (\Omega_{k i}) + \left( e^{-i \hat{H}_{0} x} \right)_{i K} (\Omega_{K i}) = e^{-i h_{i} x} (\O...
1,279
2,269
1,900
1,380
null
null
github_plus_top10pct_by_avg
2,2)$-position (because $T$ is not $d$-bad). So we can repeat the above argument and show that that there is a tableau $T'\domby T$ such that ${\hat\Theta_{T'}}$ occurs in $\theta$; contradiction. We now know that every semistandard homomorphism occurring in $\theta$ has at least two $2$s in the second row. This means...
1,280
1,455
1,177
1,189
681
0.80236
github_plus_top10pct_by_avg
by stacking the $n-k+j-1$ eigenvectors associated to the smallest eigenvalues. Computation of constraints of the $l_1$ minimization problem Compute $T=V_{2,n}^t$ Compute $W=T^{-Index[j]}$ and $w=T^{Index[j]}$(where $T^{Index[j]}$ is the column $Index[j]$ of $T$ and $V^{-I_j}$ the matrix $T$ wihtout the column $Index[j]...
1,281
577
723
1,372
1,857
0.785017
github_plus_top10pct_by_avg
x_k\tilde x_l\biggr)+ \biggl(\sum_m \tilde x_m\biggr)\biggl(\sum_{\substack{{k,l}\\k<l}}x_k x_l\biggr)\leq\sum_k x_k^2\biggl(\sum_{\substack{m\\m\neq k}}\tilde x_m\biggr)+\sum_{\substack{{k,l}\\k<l}}x_kx_l\biggl(\sum_{\substack{m\\m\neq k}}\tilde x_m+\sum_{\substack{m\\m\neq l}}\tilde x_m\biggr).$$ The right hand side ...
1,282
1,287
1,491
1,332
null
null
github_plus_top10pct_by_avg
and $33$% for $A_1$ units ($p < 0.0005$). For $R_1$ units, the median %LS decrease was $2$% ($p=0.18$). Indeed, the average $R_1$ response did not exhibit much length suppression (see Supplement), though, there were particular examples with a strong effect. #### Sequence Learning Effects in Visual Cortex Predictions...
1,283
879
1,923
886
3,527
0.771752
github_plus_top10pct_by_avg
_{c_{\k\sigma} ,d^\dagger_\sigma}(z) &=& V_k G_{d_\sigma,d^\dagger_\sigma}(z) \\ && \nonumber +\lambda_c \frac{V_k}{V_0} N_\sigma(z) .\end{aligned}$$ The off-diagonal composite correlation function $$\begin{aligned} N_\sigma(z) &=& G_{\hat X_0 c_{0\sigma} ,d^\dagger_\sigma}(z)\end{aligned}$$ accounts for the correla...
1,284
1,419
1,553
1,229
2,677
0.777926
github_plus_top10pct_by_avg
of the diagonal with two copies of $Z$, one of which maps as $$(p_1,p_2):Z\to Y_1\times Y_2\subset \bigl( Y_1\amalg Y_2\bigr) \times \bigl( Y_1\amalg Y_2\bigr),$$ the other its symmetric pair. The categorical quotient $\bigl(\bigl( Y_1\amalg Y_2\bigr)/R\bigr)^{cat}$ is also the universal push-out of $Y_1\stackrel{p_1}...
1,285
1,374
1,310
1,215
2,491
0.779352
github_plus_top10pct_by_avg
ae} j_{\bar z}^d (w) \nonumber \\ & = - c_- {f^{ac}}_g (c_2-g) j_{\bar z}^g (w)+ c_+ {f^{ac}}_g c_4 j_{\bar z}^g(w) -i (-1)^a (-1)^a {f^{ac}}_{g} \tilde{c} j_{\bar z}^g (w)\end{aligned}$$ which also vanishes thanks to the relation : $$\begin{aligned} -c_- (c_2-g) + c_+ c_4 - i \tilde{c} &=& 0.\end{aligned}$$ 3\. Ther...
1,286
1,965
1,499
1,244
null
null
github_plus_top10pct_by_avg
isms to graded $R_{\mathbb{Z}}$-module homomorphisms, $\Phi$ is a functor. Conversely, suppose that $\widetilde{N}\in R_{\mathbb{Z}}{\text{-}{\textsf}{qgr}}$ and pick a preimage $N\in R_{\mathbb{Z}}{{\textsf}{\text{-}grmod}}$. Then $N$ is generated by $\bigoplus_{i=0}^a N_i$, for some $a$, and so $N_j=R_{ja}N_a$, for ...
1,287
1,036
844
1,268
3,569
0.771502
github_plus_top10pct_by_avg
eq{\vbx'-z{|\!|\!|}}\vee{\vbz-y'{|\!|\!|}}$. Suppose that ${\vbx-z{|\!|\!|}}\leq{\vbz-y{|\!|\!|}}$ and ${\vbx'-z{|\!|\!|}}\leq{\vbz-y'{|\!|\!|}}$. Then, by [(\[eq:conv\])]{} with $a=b=q$, the contribution from this case is bounded by $$\begin{aligned} \frac{2^{2q}}{{\vbx-y{|\!|\!|}}^q{\vbx'-y'{|\!|\!|}}^q}\sum_z\frac1{...
1,288
918
994
1,389
3,970
0.768903
github_plus_top10pct_by_avg
mm} \put(20,40){\line (1,0){20}} \put(80,40){\line(1,0){20}} \qbezier(40,40)(40,10)(70,10) \qbezier(70,10)(100,10)(100,40) \put(160,40){\line (1,0){20}} \put(220,40){\line(1,0){20}} \qbezier(180,40)(180,70)(210,70) \qbezier(210,70)(240,70)(240,40) \end{picture}$$ with order two group of automorphisms each. Thus, they ...
1,289
596
1,924
1,401
null
null
github_plus_top10pct_by_avg
in by giving a general context for all three results. {#tens-defn-sect} For fixed $i\geq j\geq 0$ we are interested in the following tensor product decompositions $$\label{tensor-1} B_{ij}\cong Q_{c+i-1}^{c+i}\otimes Q_{c+i-2}^{c+i-1}\otimes\cdots \otimes Q_{c+j}^{c+j+1},$$ $$\label{tensor-101} N(i)\cong Q_{c+i-1}^...
1,290
833
1,479
1,201
1,766
0.785863
github_plus_top10pct_by_avg
e{R}}$. From ${{\Psi}\negmedspace\mid\negmedspace{R}} \subseteq \Phi$ and $\Phi \subseteq {{\Psi}\negmedspace\mid\negmedspace{R}}$ we infer $\Phi = {{\Psi}\negmedspace\mid\negmedspace{R}}$. \[L:SUBSET\_SUBSPACE\] Let $\Psi$ and $\Phi$ be ensembles. If $\Phi \subseteq \Psi$, then ${\prod{\Phi}}$ is a subspace of ${\pr...
1,291
504
961
1,342
null
null
github_plus_top10pct_by_avg
tcome, two died without requiring dialysis, and their uNGAL levels decreased within 48 h (details in Table [3](#Tab3){ref-type="table"} and Supplemental Table [7](#MOESM2){ref-type="media"}).Table 3Association between tracheotomy and discharge modality with regard to patients suffering from AKI with and without require...
1,292
3
1,379
1,622
3,511
0.771854
github_plus_top10pct_by_avg
at\beta(\hat{S})=\overline{Y}(\hat{S})$ for $2n$ (non-splitting) and $n$ (splitting). In this example we see that indeed, the splitting estimator suffers a larger risk. In this example, $D=1,000$, $n=50$, and $\beta = (a,0,\ldots, 0)$. The horizontal axis is $a$ which is the gap between the largest and second largest m...
1,293
91
1,801
1,427
null
null
github_plus_top10pct_by_avg
E}\left[\left.{g}(X_{\sigma_D}) + \int_0^{\sigma_{B(x')}} {f}(X_s)\,{\rm d}s + \int_{\sigma_{B(x')}}^{\sigma_D} {f}(X_s)\,{\rm d}s\right|\mathcal{F}_{\sigma_{B(x')}}\right]\right] \notag\\ & = \mathbb{E}_x\left[\upsilon (X_{\sigma_{B(x')}}) + \int_0^{\sigma_{B(x')}} {f}(X_s)\...
1,294
2,546
1,164
1,205
3,195
0.774113
github_plus_top10pct_by_avg
instantaneous capacity of a MIMO system whose channel matrix has correlated zero-mean complex Gaussian entries can be approximated by a Gaussian variable [@Moustakas_03_Mctccitpocian; @Martin_03_aedacfcucf]. Based on the discussion above, the distribution of $R_{\psi}$ is approximated by a Gaussian distribution, and th...
1,295
769
1,853
1,344
2,464
0.779547
github_plus_top10pct_by_avg
] Let $G^{\ddag}$ be the subfunctor of $ \mathrm{Ker~}\tilde{\varphi}/\tilde{M}^1$ consisting of those $m$ satisfying Equations (\[ea20\]), (\[ea22\]), (\[24\]), (\[24’\]), (\[ea25\]), (\[ea27\]), and (\[ea32\]). Note that such $m$ also satisfies Equation (\[32’\]). Then $G^{\ddag}$ is represented by a smooth closed su...
1,296
581
1,890
1,340
2,756
0.777245
github_plus_top10pct_by_avg
{{\widehat{S}}}$: Get $\hat\beta_{{\widehat{S}}}$ from ${\cal D}_{2,n}$ by least squares. Output $\hat{C}_{{\widehat{S}}} = \bigotimes_{j\in {\widehat{S}}} C(j)$ where $C(j) = \hat\beta_{{\widehat{S}}}(j) \pm z_{\alpha/(2k)} \sqrt{\hat\Gamma_n(j,j)}$ where $\hat\Gamma$ is given by (\[eq::Ga\]). For $\gamma_{{\wideha...
1,297
694
1,044
1,239
null
null
github_plus_top10pct_by_avg
\^[i]{}\_[( \^[-1]{} )]{}\^\_\_i=b\^. Note that the expression $\Phi^{-1}\frac{{\partial}f}{{\partial}r}\in {\mathbb{R}}^q$ is a contravariant vector as well as $b\in{\mathbb{R}}^q$. Hence there exists a nonzero scalar function $\Omega=\Omega(x,u)$, a rotation matrix $L=L(x,u)\in SO(q)$ and a vector $\tau=\tau(x,u)\i...
1,298
1,934
2,176
1,361
null
null
github_plus_top10pct_by_avg
,0}$ have degree 0, 2 or 4 in $x$. Since $f$ contains summands of only 2-nd and 4-th degree in $x$, we have $\phi_{1,1}+\phi_{1,3}+\phi_{2,1}=0$. Therefore, $\phi=\phi_{1,0}+\phi_{1,2}+\phi_{2,0}$. Since $x$ is the central letter of the dipolynomial $f$, central letters of dimonomials from $\phi$ can be variables $x$...
1,299
2,761
1,717
1,285
null
null
github_plus_top10pct_by_avg
s a normal subgroup of $G=N{{\operatorname}{C}_{G}(y)}$. Since $N$ is a minimal normal subgroup of $G$, we deduce that either $N={{\operatorname}{C}_{N}(y)}$ or ${{\operatorname}{C}_{N}(y)}=1$. The first case yields to the contradiction $G={{\operatorname}{C}_{G}(y)}$. So we may assume ${{\operatorname}{C}_{N}(y)}=1$. ...
1,300
594
1,045
1,183
null
null
github_plus_top10pct_by_avg