斯坦福大学、北航、深圳华大基因研究所的研究人员在《Environmental Science and Technology》期刊上发表论文，报告粉虱内脏中的微生物能安全降解多种塑料。难以降解的塑料是地球环境面临的一大难题。以泡沫塑料杯为例，美国人每年要扔掉25亿个塑料杯，但塑料杯只是美国人每年产生的3300万吨塑料垃圾的很小一部分。这些塑料垃圾只有不到10%被回收，其余留在环境中的则会导致水污染和动物中毒等种种问题。研究人员发现，粉虱能消化泡沫聚苯乙烯和其它类型的聚苯乙烯材料。论文合作者、斯坦福的Wei-Min Wu说，我们的发现开启了一扇解决全球塑料污染问题之门。他们的论文首次给出了这种蠕虫内脏微生物生物降解塑料的详细证据。

1d
阿ZF称已收复昆都士
（德国之声中文网）阿富汗内政部发言人塞迪基（Sedik Sedikki）通过推特宣布，"特殊部队现在已控制昆都士这座城市"，塔利班"损失惨重"，昆都士"现在将清理恐怖分子"。 多名昆都士居民对法新社表示，昨天（9月30日）夜里，发生炮击。在这个北部城市，现已可看到阿富汗ZF军士兵身影，街上横七竖八躺着塔利班武装分子的尸体，ZF军士兵在市中心升起了阿富汗国旗，取代了此前一度在那里飘扬的塔利班旗帜。

'Here we go again' _ Americans' lament after Oregon shooting

By Susan Cornwell and Richard Cowan WASHINGTON (Reuters) - President Barack Obama on Friday urged the U.S. Congress to take steps soon to fund the federal government in 2016 and raise its nearly exhausted borrowing authority, but acknowledged that Republican political turmoil in Congress will complicate that. "I will not sign another shortsighted spending bill," Obama told reporters, warning that a temporary budget patch approved this week by lawmakers presents the risk of a new fiscal crisis before Christmas. On Wednesday, just hours before a midnight deadline when government agency funds were due to run out, Congress extended current spending levels through Dec. 11.

By Susan Cornwell and Richard Cowan WASHINGTON (Reuters) - President Barack Obama on Friday urged the U.S. Congress to take steps soon to fund the federal government in 2016 and raise its nearly exhausted borrowing authority, but acknowledged that Republican political turmoil in Congress will complicate that. "I will not sign another shortsighted spending bill," Obama told reporters, warning that a temporary budget patch approved this week by lawmakers presents the risk of a new fiscal crisis before Christmas. On Wednesday, just hours before a midnight deadline when government agency funds were due to run out, Congress extended current spending levels through Dec. 11.

WASHINGTON (AP) — President Barack Obama is accusing White House hopefuls of concocting "half-baked" ideas for stemming the crisis in Syria.

由今日开始 Google 正式完成架构重组，其亦随即成为了 Alphabet 旗下的其中一间子公司了。不过其实对于普通用户来说，这次重组的影响其实不大，大部份 Google 旗下的公司都会维持原状，就只有开发《Ingress》游戏的 Niantic Labs 独立出来。同时，在架构重组之后，Google 本来的核心业务会变由 Sundar Pichai 打理，而两位爱玩的创办人 Sergey Brin 和 Larry Page 则会聚焦于 Google X 这个创立新业务的部门。[图片来源...

多年来从不缺席台湾设计师周的华硕，今年倒是跳出了贯往以 Zen 系列为主角的传统，而是改为展示 ROG 系列的产品，并将摊位布置成了和往常不一样的张扬形象。当然大部份参观的人大概会被华硕布置的大型设备艺术（一个用闪光灯的效果将波形的水柱「定格」在空中的效果）给吸引过去，但我们则是立即看到了华硕在 IFA 上推出的那台自带水冷设备的笔记本。据华硕的说明，这台 GX700 目前还是在原型机的阶段，可能采取的方案是在笔记本内放入桌电级的显示芯片（例如 GTX980），但只有插上水冷底座时才会跑全速，笔...

GUATEMALA CITY — A rain-sodden hillside about 300 feet (100 meters) high collapsed onto a neighborhood on the outskirts of Guatemala's capital with a roar and wave of sudden darkness, killing at least 26 people and sending 36 to hospitals.

明太祖洪武二十一年（1388年），即欲修纂類書，商議“編輯經史百家之言為《類要》”，但未修成。明成祖即位後，為整理知識，令解縉等人修書。編撰宗旨：“凡書契以來經史子集百家之書，至於天文、地誌、陰陽、醫卜、僧道、技藝之言，備輯為一書，毋厭浩繁！”過程召集147人，首次成書於永樂二年（1404年），初名《文獻集成》；明成祖過目後認為“所纂尚多未備”，不甚滿意。永樂三年（1405年）再命太子少傅姚廣孝、解縉、禮部尚書鄭賜監修以及劉季篪等人重修，動用朝野上下共2,169人編寫。組織設監修、總裁、副總裁、都總裁等職，負責各方面工作。蔣用文、趙同友各為正副總裁，陳濟為都總裁[2]，參用南京文淵閣的全部藏書，永樂五年（1407年）定稿進呈，明成祖看了十分滿意，親自為序，並命名為《永樂大典》，清抄至永樂六年（1408年）冬天才正式成書。据《进永乐大典表》稱，全书缮写成22,877卷，目录60卷，成書11,095册。

《永樂大典》修書過程中，對收錄書籍未做任何修改，採用兼收並取方式，保持書籍原始內容。但據專家表示，《永樂大典》有不少错漏，并非如人所誉“不曾擅减片语”，謝保成即指出《永乐大典》卷一九六三七“目”字韵下“医目”条引《唐语林》，原文出自《因话录》卷六《羽部》，《永乐大典》随意删改此文的情况非常严重，连“善医者沈师象”也讹作“喜医者沉大师象”。[3]

永樂年間修訂的《永樂大典》原書只有一部，現今存世的皆為嘉靖年間的抄本。明世宗十分喜歡《永樂大典》，經常隨身攜帶，翻閱查找驗方。嘉靖四十一年八月下令抄寫了一部。[4]隆庆初告成，原本歸還南京[5]。其正本贮文渊阁，副本别贮皇史宬[6]。這套書到乾隆年間存有8,000冊，。對於原書的去向一直是一個不解之謎，歷史學界有多種猜測。顧炎武《日知錄》斷定大典“全部皆佚”。另一個猜測是，原書已給嘉靖皇帝殉葬。嘉靖駕崩後沒有馬上入葬而是等了很久[7]，當時抄本正在進行中，张忱石《〈永乐大典〉正本之谜》：“归纳起来，正本下落大体上存在五种说法。首先，毁于清乾清宫大火……其次，毁于明亡之际……第三，毁于明万历宫中火灾说……第四，藏皇史宬夹墙说……第五，殉葬说。……由于明世宗对《永乐大典》‘殊宝爱之’，笔者认为极有可能正本为其殉葬于永陵……”

thanks

10月3日，央视《新闻联播》、《朝闻天下》、《新闻30分》、《新闻直播间》等栏目重磅推出一档全新大型数据新闻节目——《数说命运共同体》，节目挖掘超过1亿GB的数据，分析发现“一带一路”沿线国家40多亿百姓休戚相关的密切联系，披露大量不为人知的新鲜内容，炫酷的视频技术令观众耳目一新。

The effectiveness of revenue management systems has diminished in recent years due to the systems' inability to address the increasing complication of online deal-seeking behavior. To restore their efficiency, one must first understand the changes in advanced-booking behavior and their implications. This study expands the consumer booking model by addressing the impact of time-before-the-date-of-stay and exploring the implication for the hotel's pricing/marketing strategies. The findings underscore the urgent need for empirical research on timing by showing that the predictions of the advanced-booking model, and consequently the effectiveness of RM systems, depend on the actual patterns over time.

If you're looking for a graphing calculator app that works smoothly and seamlessly, you've found it! Graphing Calculator by Mathlab is a scientific graphing calculator integrated with algebra and is an indispensable mathematical tool for students in elementary school to those in college or graduate school, or just anyone who needs more than what a basic calculator offers. It is designed to replace bulky and costly handheld graphing calculators and works on virtually any Android phone or tablet.

The Hausdorff distance (HD) between two point sets is a commonly used dissimilarity measure for comparing point sets and image segmentations. Especially when very large point sets are compared using the HD, for example when evaluating magnetic resonance volume segmentations, or when the underlying applications are based on time critical tasks, like motion detection, then the computational complexity of HD algorithms becomes an important issue. In this paper we propose a novel efficient algorithm for computing the exact Hausdorff distance. In a runtime analysis, the proposed algorithm is demonstrated to have nearly-linear complexity. Furthermore, it has efficient performance for large point set sizes as well as for large grid size; performs equally for sparse and dense point sets; and finally it is general without restrictions on the characteristics of the point set. The proposed algorithm is tested against the HD algorithm of the widely used national library of medicine insight segmentation and registration toolkit (ITK) using magnetic resonance volumes with extremely large size. The proposed algorithm outperforms the ITK HD algorithm both in speed and memory required. In an experiment using trajectories from a road network, the proposed algorithm significantly outperforms an HD algorithm based on R-Trees.

Conventional learning-based methods for segmenting prostate in CT images ignore the relations among the low-level features by assuming all these features are independent. Also, their feature selection steps usually neglect the image appearance changes in different local regions of CT images. To this end, we present a novel semi-automatic learning-based prostate segmentation method in this article. For segmenting the prostate in a certain treatment image, the radiation oncologist will be first asked to take a few seconds to manually specify the first and last slices of the prostate. Then, prostate is segmented with the following two steps: (i) Estimation of 3D prostate-likelihood map to predict the likelihood of each voxel being prostate by employing the coupled feature representation, and the proposed Spatial-COnstrained Transductive LassO (SCOTO); (ii) Multi-atlases based label fusion to generate the final segmentation result by using the prostate shape information obtained from both planning and previous treatment images. The major contribution of the proposed method mainly includes: (i) incorporating radiation oncologist’s manual specification to aid segmentation, (ii) adopting coupled features to relax previous assumption of feature independency for voxel representation, and (iii) developing SCOTO for joint feature selection across different local regions. The experimental result shows that the proposed method outperforms the state-of-the-art methods in a real-world prostate CT dataset, consisting of 24 patients with totally 330 images, all of which were manually delineated by the radiation oncologist for performance evaluation. Moreover, our method is also clinically feasible, since the segmentation performance can be improved by just requiring the radiation oncologist to spend only a few seconds for manual specification of ending slices in the current treatment CT image.

Subspace-based methods are known to provide a practical solution for image set-based object recognition. Based on the insight that local shape differences between objects offer a sensitive cue for recognition, this paper addresses the problem of extracting a subspace representing the difference components between class subspaces generated from each set of object images independently of each other. We first introduce the difference subspace (DS), a novel geometric concept between two subspaces as an extension of a difference vector between two vectors, and describe its effectiveness in analyzing shape differences. We then generalize it to the generalized difference subspace (GDS) for multi-class subspaces, and show the benefit of applying this to subspace and mutual subspace methods, in terms of recognition capability. Furthermore, we extend these methods to kernel DS (KDS) and kernel GDS (KGDS) by a nonlinear kernel mapping to deal with cases involving larger changes in viewing direction. In summary, the contributions of this paper are as follows: 1) a DS/KDS between two class subspaces characterizes shape differences between the two respectively corresponding objects, 2) the projection of an input vector onto a DS/KDS realizes selective visualization of shape differences between objects, and 3) the projection of an input vector or subspace onto a GDS/KGDS is extremely effective at extracting differences between multiple subspaces, and therefore improves object recognition performance. We demonstrate validity through shape analysis on synthetic and real images of 3D objects as well as extensive comparison of performance on classification tests with several related methods; we study the performance in face image classification on the Yale face database B+ and the CMU Multi-PIE database, and hand shape classification of multi-view images.

DNA methylation studies have been revolutionized by the recent development of high throughput array-based platforms. Most of the existing methods analyze microarray methylation data on a probe-by-probe basis, ignoring probe-specific effects and correlations among methylation levels at neighboring genomic locations. These methods can potentially miss functionally relevant findings associated with genomic regions. In this article, we propose a statistical model that allows us to pool information on the same probe across multiple samples to estimate the probe affinity effect, and to borrow strength from the neighboring probe sites to better estimate the methylation values. Using a simulation study, we demonstrate that our method can provide accurate model-based estimates. We further use the proposed method to develop a new procedure for detecting differentially methylated regions, and compare it with a state-of-the-art approach via a data application.

There is an overwhelmingly large literature and algorithms already available on “large-scale inference problems” based on different modeling techniques and cultures. Our primary goal in this article is not to add one more new methodology to the existing toolbox but instead (i) to clarify the mystery how these different simultaneous inference methods are connected, (ii) to provide an alternative more intuitive derivation of the formulas that leads to simpler expressions in order (iii) to develop a unified algorithm for practitioners. A detailed discussion on representation, estimation, inference, and model selection is given. Applications to a variety of real and simulated datasets show promise. We end with several future research directions.

Papers evaluating measures of explained variation, or similar indices, almost invariably use independence from censoring as the most important criterion. And they always end up suggesting that some measures meet this criterion, and some do not, most of the time leading to a conclusion that the first is better than the second. As a consequence, users are offered measures that cannot be used with time-dependent covariates and effects, not to mention extensions to repeated events or multi-state models. We explain in this paper that the aforementioned criterion is of no use in studying such measures, because it simply favors those that make an implicit assumption of a model being valid everywhere. Measures not making such an assumption are disqualified, even though they are better in every other respect. We show that if these, allegedly inferior, measures are allowed to make the same assumption, they are easily corrected to satisfy the ‘independent-from-censoring’ criterion. Even better, it is enough to make such an assumption only for the times greater than the last observed failure time τ, which, in contrast with the ‘preferred’ measures, makes it possible to use all the modeling flexibility up to τ and assume whatever one wants after τ. As a consequence, we claim that some of the measures being preferred as better in the existing reviews are in fact inferior. Copyright © 2015 John Wiley & Sons, Ltd.

Repeated structures such as building facades, fences or road markings often represent a significant challenge for place recognition. Repeated structures are notoriously hard for establishing correspondences using multi-view geometry. They violate the feature independence assumed in the bag-of-visual-words representation which often leads to over-counting evidence and significant degradation of retrieval performance. In this work we show that repeated structures are not a nuisance but, when appropriately represented, they form an important distinguishing feature for many places. We describe a representation of repeated structures suitable for scalable retrieval and geometric verification. The retrieval is based on robust detection of repeated image structures and a suitable modification of weights in the bag-of-visual-word model. We also demonstrate that the explicit detection of repeated patterns is beneficial for robust visual word matching for geometric verification. Place recognition results are shown on datasets of street-level imagery from Pittsburgh and San Francisco demonstrating significant gains in recognition performance compared to the standard bag-of-visual-words baseline as well as the more recently proposed burstiness weighting and Fisher vector encoding.

Geometric Change Detection in Urban Environments Using Images
We propose a method to detect changes in the geometry of a city using panoramic images captured by a car driving around the city. The proposed method can be used to significantly optimize the process of updating the 3D model of an urban environment that is changing over time, by restricting this process...

号贩子倒卖号子和抢钱一样，问题是他们抢了谁的钱？看起来好像是抢了患者的钱，其实不然。一个医生的号子，被患者竞价之后为 1 000 元，这个钱本应属于医院和医生，但因为公家挂号费限价而不得不通过号贩子完成交易，这是政策实实在在的在帮号贩子抢医生的钱。与其让号贩子赚，为什么不医院收回来，补贴给医生和患者？所谓「为了维持公立医院的公益性」，结果就是号贩子获益，患者和医生双输。

普遍认为号子是公共资源，应该公平分配，人为控制的超低挂号费价格导致现在的公平分配方式就是：排队挂号。如果高价（价高者得）被认为是对穷人的歧视，那么排队就是「先到先得」的歧视，是对没有时间排队人的歧视。并且这真的对穷人公平吗？穷人排队没有号贩子专业，有钱人可以顾人排队还可以从号贩子手里买号子，有权的人可以通过其他途径拿到号子（权力歧视）。

经济学奖（The Prize in Economic Sciences）：2015 年 10 月 12 日下午 1:00（北京时间 10 月 12 日 19：00）

Medicine Laureates


1.
May-Britt Moser

2.
Sir Alexander Fleming

3.
John O'Keefe

4.
Ivan Pavlov

5.
James Watson

6.
Edvard I. Moser

7.
Frederick G. Banting

8.
Robert Koch

9.
Otto Warburg

10.
Francis Crick

Nominations for the 2015 Nobel Prize in Physiology or Medicine
327 scientists have been nominated for the 2015 Nobel Prize in Physiology or Medicine. Among them, 57 individuals were nominated for the first time. The deadline for nominations for the 2015 Nobel Prize was 31 January.

Live Webcast of the 2015 Nobel Prize Announcements
PHYSIOLOGY OR MEDICINE - Monday 5 October, 11:30 a.m. at the earliest
PHYSICS - Tuesday 6 October, 11:45 a.m. at the earliest
CHEMISTRY - Wednesday 7 October, 11:45 a.m. at the earliest
PEACE - Friday 9 October, 11:00 a.m.
ECONOMIC SCIENCES - Monday 12 October, 1:00 p.m. at the earliest
LITERATURE - The date will be set later
Times listed are local time in Sweden.