3,120 research outputs found
He is our master : Jesus in the Thought of Swami Prabhupada
Now that steam, electricity, and the printing press have brought into closer communication the different races that inhabit the earth, and have expanded the minds of men, tending to dispel the illusion that God Almighty especially favours any particular people, it is time to proclaim to the world, that if a messenger of God appeared in Judea about nineteen hundred years ago, it is no less true that a messenger from the same God appeared in the quiet town of Navadweep (popularly known as Nadia) in Bengal, some fifteen centuries later. The former is known by the name of Jesus Christ; the latter is known in India by the name of Sree Gauranga, Sree Krishna Chaitanya, and several other names. If wonders attended Jesus, so also they attended Sree Gauranga of Nadia.
The Christians have conferred an inestimable obligation upon those Hindus whose faith has been affected by Western materialism, by presenting Christ to them; and they, as a grateful return, are anxious to present Sree Krishna and Sree Gauranga to the people of the West.
So begins Shishir Kumar Ghose\u27s lengthy biography of Caitanya, published at the turn of the twentieth century
VIEWPOINT: Hinduism and the Academy: Towards a Dialogue Between Scholar and Practitioner
Gupta articlulates a rationale as to why the position of both the academician and the practitioner are necessary for meaningful religious dialog
Robust and MaxMin Optimization under Matroid and Knapsack Uncertainty Sets
Consider the following problem: given a set system (U,I) and an edge-weighted
graph G = (U, E) on the same universe U, find the set A in I such that the
Steiner tree cost with terminals A is as large as possible: "which set in I is
the most difficult to connect up?" This is an example of a max-min problem:
find the set A in I such that the value of some minimization (covering) problem
is as large as possible.
In this paper, we show that for certain covering problems which admit good
deterministic online algorithms, we can give good algorithms for max-min
optimization when the set system I is given by a p-system or q-knapsacks or
both. This result is similar to results for constrained maximization of
submodular functions. Although many natural covering problems are not even
approximately submodular, we show that one can use properties of the online
algorithm as a surrogate for submodularity.
Moreover, we give stronger connections between max-min optimization and
two-stage robust optimization, and hence give improved algorithms for robust
versions of various covering problems, for cases where the uncertainty sets are
given by p-systems and q-knapsacks.Comment: 17 pages. Preliminary version combining this paper and
http://arxiv.org/abs/0912.1045 appeared in ICALP 201
Generic Drug Policy In The U.s. - Impact On Drug Prices And Shortages
Generic medicines offer a significantly cheaper alternative to brand-name drugs and have become an indispensable means of maintaining patient access and adherence to treatments. In recent years, as a result of monopolistic and oligopolistic conditions, generic drugs have begun to increase in price, sometimes exorbitantly. The competitiveness of drug markets with respect to the number of generic manufacturers and the implications for drug prices and shortages have not been systematically studied.
Two main analyses are presented in this study. First, using publicly available information, the timing of generic drug approvals and the total number of generic manufacturers for all small-molecule drugs approved between 1984 and 2015 were characterized. Second, this study investigated the impact on drug prices and shortages of a specific FDA regulation, called the Unapproved Drugs Initiative.
The first analysis demonstrates that among 417 FDA-approved drugs, 210 were eligible for generic competition, and 77 (37%) had three or fewer generic drugs approved: 16 had three generic approvals, 9 had two, 16 had one, and 36 had zero. Among the 174 drugs with at least one generic approval, the median number of generic approvals was 7 (IQR, 4-12). Generic approvals were fewer among orphan-designated drugs when compared with non-orphan-designated drugs (18 of 33 [55%] vs. 156 of 177 [88%]; p\u3c0.001).
The second analysis found that since 2006, 34 unapproved prescription drugs had been addressed by the Unapproved Drugs Initiative (UDI). Nearly 90% of those that went on to receive FDA approval were supported by literature reviews or bioequivalence studies, not new clinical trials. In addition, once targeted by the UDI, drugs experienced price and shortage increases of nearly 40% and 74%, respectively.
Overall, more than one-third of drugs approved after 1984 and without protection from patents have three or fewer generic competitors, making them vulnerable to price increases. By unintentionally reducing the number of manufacturers for specific drugs, the FDA’s Unapproved Drugs Initiative led to higher prices and more frequent and longer shortages, highlighting the importance of robust generic competition.
In conclusion, insufficient pharmaceutical competition has created an environment enabling price increases of old, off-patent generic drugs, such as Daraprim and Epipen. This study highlights that a substantial number of additional, similar drugs is vulnerable to such price increases for a variety of reasons. Future efforts to reform generic drug policy should seek to boost generic competition, more carefully regulate drug prices, and address brand-name pharmaceutical companies’ strategies to obstruct the ability of generic manufacturers to compete. In addition, physicians and patients should be bettered educated on the fact that a lack of generic competitors may mean that simply prescribing generic drugs will not make medications affordable for patients; alternative options may have to be explored. Such efforts are essential in ensuring continued patient access to affordable drugs
Dial a Ride from k-forest
The k-forest problem is a common generalization of both the k-MST and the
dense--subgraph problems. Formally, given a metric space on vertices
, with demand pairs and a ``target'' ,
the goal is to find a minimum cost subgraph that connects at least demand
pairs. In this paper, we give an -approximation
algorithm for -forest, improving on the previous best ratio of
by Segev & Segev.
We then apply our algorithm for k-forest to obtain approximation algorithms
for several Dial-a-Ride problems. The basic Dial-a-Ride problem is the
following: given an point metric space with objects each with its own
source and destination, and a vehicle capable of carrying at most objects
at any time, find the minimum length tour that uses this vehicle to move each
object from its source to destination. We prove that an -approximation
algorithm for the -forest problem implies an
-approximation algorithm for Dial-a-Ride. Using our
results for -forest, we get an -
approximation algorithm for Dial-a-Ride. The only previous result known for
Dial-a-Ride was an -approximation by Charikar &
Raghavachari; our results give a different proof of a similar approximation
guarantee--in fact, when the vehicle capacity is large, we give a slight
improvement on their results.Comment: Preliminary version in Proc. European Symposium on Algorithms, 200
Approximation Algorithms for Correlated Knapsacks and Non-Martingale Bandits
In the stochastic knapsack problem, we are given a knapsack of size B, and a
set of jobs whose sizes and rewards are drawn from a known probability
distribution. However, we know the actual size and reward only when the job
completes. How should we schedule jobs to maximize the expected total reward?
We know O(1)-approximations when we assume that (i) rewards and sizes are
independent random variables, and (ii) we cannot prematurely cancel jobs. What
can we say when either or both of these assumptions are changed?
The stochastic knapsack problem is of interest in its own right, but
techniques developed for it are applicable to other stochastic packing
problems. Indeed, ideas for this problem have been useful for budgeted learning
problems, where one is given several arms which evolve in a specified
stochastic fashion with each pull, and the goal is to pull the arms a total of
B times to maximize the reward obtained. Much recent work on this problem focus
on the case when the evolution of the arms follows a martingale, i.e., when the
expected reward from the future is the same as the reward at the current state.
What can we say when the rewards do not form a martingale?
In this paper, we give constant-factor approximation algorithms for the
stochastic knapsack problem with correlations and/or cancellations, and also
for budgeted learning problems where the martingale condition is not satisfied.
Indeed, we can show that previously proposed LP relaxations have large
integrality gaps. We propose new time-indexed LP relaxations, and convert the
fractional solutions into distributions over strategies, and then use the LP
values and the time ordering information from these strategies to devise a
randomized adaptive scheduling algorithm. We hope our LP formulation and
decomposition methods may provide a new way to address other correlated bandit
problems with more general contexts
Understanding Type Ia Supernovae Through Their Host Galaxies Using the SDSS-II Supernova Survey
The recent discovery of the accelerating expansion of the Universe and thus the existence of dark energy was made possible by the study of Type Ia supernovae. These thermonuclear explosions of white dwarfs are excellent standardizable candles that can be seen out to great distances and used to constrain cosmological parameters. However, in an era when modern surveys are discovering hundreds of Type Ia supernovae and upcoming surveys plan to find thousands more, we are no longer limited by statistics, but are now being limited by systematic uncertainties in supernova cosmology. Among these systematic uncertainties are the nature of the supernova progenitor and the effect of the environment on the progenitor. An excellent way to probe these systematics is through the study of the galaxies that host Type Ia supernovae. Correlations have been found between supernova properties and the physical properties of their host galaxies such as mass, metallicity, and star formation rate. In this dissertation, I use supernovae from the full three-year Sloan Digital Sky Survey II (SDSS-II) Supernova Survey and multi-wavelength photometry of their host galaxies to find evidence of a correlation between supernova luminosities and the age of their hosts, a possible proxy for progenitor age. I also detail a method of host galaxy identification, tested and applied to the many thousands of SDSS-II supernova candidates, which will be published in the upcoming final data release of the Supernova Survey. In addition, I present work in which I compute the luminosity functions for Type Ia supernovae and their host galaxies. This work and continuing work in this vein can help shed light on the nature of dark energy and improve the utility of Type Ia supernovae as cosmological distance indicators
- …