BACKGROUND Lower limb lymphedema (LLL) is a chronic and incapacitating condition afflicting patients who undergo lymphadenectomy for gynecologic cancer. This study aimed to identify risk factors for LLL and to develop a prediction model for its occurrence. METHODS Pelvic lymphadenectomy (PLA) with or without para-aortic lymphadenectomy (PALA) was performed on 366 patients with gynecologic mal...

We devise an algorithm, e L, with the following specifications: It takes as input an arbitrary basis B = (bi)i ∈ Zd×d of a Euclidean lattice L; It computes a basis of L which is reduced for a mild modification of the Lenstra-Lenstra-Lovász reduction; It terminates in time O(dβ + dβ) where β = log max ‖bi‖ (for any ε > 0 and ω is a valid exponent for matrix multiplication). This is the first LLL...

Given a matrix A ∈ Zm×n satisfying certain regularity assumptions, a wellknown integer programming problem asks to find an integer point in the associated knapsack polytope P(A,b)= {x ∈R≥0 :Ax = b} or determine that no such point exists. We obtain an LLL-based polynomial time algorithm that solves the problem subject to a constraint on the location of the vector b.

Although a polynomial time algorithm exists, the most commonly used algorithm for factoring a univariate polynomial f with integer coeecients is the Berlekamp-Zassenhaus algorithm which has a complexity that depends exponentially on n where n is the number of modular factors of f. This exponential time complexity is due to a combinatorial problem; the problem of choosing the right subset of the...

OBJECTIVES Although an association between prognosis and lobar location of lung cancer, particularly the left lower lobe (LLL), has been suggested, the certainty of such association remains controversial. The purpose of this study was to evaluate the impact of tumour lobar location on surgical outcomes as an independent prognostic factor for survival in our non-small cell lung cancer (NSCLC) pa...

While there has been significant progress on algorithmic aspects of the Lovász Local Lemma (LLL) in recent years, a noteworthy exception is when the LLL is used in the context of random permutations. The breakthrough algorithm of Moser & Tardos only works in the setting of independent variables, and does not apply in this context. We resolve this by developing a randomized polynomial-time algor...

We compare Schnorr's algorithm for semi block 2k-reduction of lattice bases with Koy's primal-dual reduction for blocksize 2k. Koy's algorithm guarantees within the same time bound under known proofs better approximations of the shortest lattice vector. Under reasonable heuristics both algorithms are equally strong and much better than proven in worst-case. We combine primal-dual reduction with...

In the last two lectures we presented an algorithmic proof of the LLL (and in fact Shearer’s lemma) when the underlying probability space consists of independent random variables. In this lecture we present an “algorithmic proof” of Shearer’s Lemma for a general probability space. We note that the first abstract algorithmic framework for the LLL beyond [Moser and Tardos (2010)] was proposed by ...

Seat height that is too high (> 120% of lower leg length [LLL]) or too low (< 80% of LLL) can impede safe transfer and result in falls. This study examines the difference between LLL of frail nursing home residents and the height of their toilets and beds in the lowest position, compares the patient or environmental characteristics of those able to transfer from the bed or toilet to those who c...