A New Look at the Easy-Hard-Easy Pattern of Combinatorial Search Difficulty

The easy-hard-easy pattern in the difficulty of combinatorial search problems as constraints are added has been explained as due to a competition between the decrease in number of solutions and increased pruning. We test the generality of this explanation by examining one of its predictions: if the number of solutions is held fixed by the choice of problems, then increased pruning should lead to a monotonic decrease in search cost. Instead, we find the easy-hard-easy pattern in median search cost even when the number of solutions is held constant, for some search methods. This generalizes previous observations of this pattern and shows that the existing theory does not explain the full range of the peak in search cost. In these cases the pattern appears to be due to changes in the size of the minimal unsolvable subproblems, rather than changing numbers of solutions.Comment: See http://www.jair.org/ for any accompanying file

Management and conservation of marine fisheries resources

The present understanding of the term fishery management includes, besides conservation (avoiding over-flshing), other aspects like avoiding under-flshing of stocks, meting out social equity and affording consumer protection, mathematical models developed, based on experience In temperate waters, are of doubtful applicability in the tropical waters. Moreover, in a populous country like India, employment, economic and social aspects are the dominant considerations. In India, while fish production has increased, the unit production of both mechanised and nonmechanised sectors has dropped to about 40%, but the higher price of fish, both In the export and domestic market, is sustaining the fishing industr

Hidden variables unseen by Random Forests

Random Forests are widely claimed to capture interactions well. However, some simple examples suggest that they perform poorly in the presence of certain pure interactions that the conventional CART criterion struggles to capture during tree construction. We argue that alternative partitioning schemes can enhance identification of these interactions. Furthermore, we extend recent theory of Random Forests based on the notion of impurity decrease by considering probabilistic impurity decrease conditions. Within this framework, consistency of a new algorithm coined 'Random Split Random Forest' tailored to address function classes involving pure interactions is established. In a simulation study, we validate that the modifications considered enhance the model's fitting ability in scenarios where pure interactions play a crucial role

Detecting Natural Language Biases with Prompt-based Learning

In this project, we want to explore the newly emerging field of prompt engineering and apply it to the downstream task of detecting LM biases. More concretely, we explore how to design prompts that can indicate 4 different types of biases: (1) gender, (2) race, (3) sexual orientation, and (4) religion-based. Within our project, we experiment with different manually crafted prompts that can draw out the subtle biases that may be present in the language model. We apply these prompts to multiple variations of popular and well-recognized models: BERT, RoBERTa, and T5 to evaluate their biases. We provide a comparative analysis of these models and assess them using a two-fold method: use human judgment to decide whether model predictions are biased and utilize model-level judgment (through further prompts) to understand if a model can self-diagnose the biases of its own prediction

PAC-Bayesian Bounds for Randomized Empirical Risk Minimizers

The aim of this paper is to generalize the PAC-Bayesian theorems proved by Catoni in the classification setting to more general problems of statistical inference. We show how to control the deviations of the risk of randomized estimators. A particular attention is paid to randomized estimators drawn in a small neighborhood of classical estimators, whose study leads to control the risk of the latter. These results allow to bound the risk of very general estimation procedures, as well as to perform model selection

Bilateral Simultaneous Retinal Detachment in Pseudophakia

Cataract surgery is the most frequent surgical intervention, with approximately 700,000 operations per year in Germany alone. One of the most serious complications is retinal detachment, with a reported incidence rate of pseudophakic retinal detachment of 0.75-1.65%. We report the case of a patient who suffered from a simultaneous bilateral pseudophakic retinal detachment. Interestingly, the bilateral detachments in the left and the right eye started with only some hours' delay. He had no acute trigger for the retinal detachment and no risk factors besides the cataract surgery performed on both eyes some weeks earlier. Simultaneous bilateral retinal detachments will be more common, due to increasing numbers of cataract surgeries and the demographic development. We conclude that funduscopy should be regularly performed in mydriasis to avoid sight-threatening simultaneous bilateral retinal detachments

Bilateral Simultaneous Retinal Detachment in Pseudophakia

Cataract surgery is the most frequent surgical intervention, with approximately 700,000 operations per year in Germany alone. One of the most serious complications is retinal detachment, with a reported incidence rate of pseudophakic retinal detachment of 0.75-1.65%. We report the case of a patient who suffered from a simultaneous bilateral pseudophakic retinal detachment. Interestingly, the bilateral detachments in the left and the right eye started with only some hours' delay. He had no acute trigger for the retinal detachment and no risk factors besides the cataract surgery performed on both eyes some weeks earlier. Simultaneous bilateral retinal detachments will be more common, due to increasing numbers of cataract surgeries and the demographic development. We conclude that funduscopy should be regularly performed in mydriasis to avoid sight-threatening simultaneous bilateral retinal detachments

Coconut Inflorescence Sap Enhances Exercise Performance and Plasma Antioxidant Status in Young Active Men

Purpose Nutrition has been increasingly recognized as a key component to optimal sports performance. Though several botanical agents have been reported to possess ergogenic potential, there exists a great interest for tasty and safe natural substances as performance boosters. In the present contribution, the ergogenic potential of a novel powder form of coconut inflorescence sap (CSP) was investigated for the first time. Method Out of the fourteen participants recruited, twelve recreationally active men completed the single-blinded, placebo-controlled, crossover study for 8 weeks. Running based anaerobic sprint test (RAST) and 2.4 km running test were performed as anaerobic and aerobic tests, respectively. In arm 1, the participants were received with either placebo (200 mL water containing 400 mg aspartame/day) or CSP (3 g in 200 mL water/day) for 21 days. After the washout period, arm 2 was performed with a reversed treatment regime. VO2 max was estimated using a predictive formula. Results The primary outcome showed a significant enhancement in peak power and mean power (peak power from 3.67 W/kg b. wt. to 5.38 W/kg b. wt.; mean power from 3.47 W/kg b. wt. to 5.06 W/kg b. wt.). A significant (p \u3c 0.001) increase in VO2 max among CSP condition compared to the placebo was observed (from 59.38 ± 2.15 mL/kg/min to 62.56 ± 0.52 mL/kg/min). Further, serum analysis revealed enhanced antioxidant status and reduced lactate dehydrogenase (p \u3c 0.01) levels without any significant changes (p \u3e 0.05) in safety parameters. Conclusion It was concluded that CSP possesses significant ergogenic effect and may find wide application as a natural ingredient for sports nutrition and energy drinks. Trial Registration The study was registered in Clinical Trial Registry of India (Reg No.: CTRI/2018/03/012551 dated 13/03/2018)

Development and implementation of blood pressure screening and referral guidelines for German community pharmacists

Involvement of community pharmacists in the detection and control of hypertension improves patient care. However, current European or North‐American guidelines do not provide specific guidance how to implement collaboration between pharmacists and physicians, especially when and how to refer patients with undetected or uncontrolled hypertension to a physician. The German Society of Cardiology and the ABDA – Federal Union of German Associations of Pharmacists developed and tested referral recommendations for community pharmacists, embedded in two guideline worksheets. The project included a guideline‐directed blood pressure (BP) measurement and recommendations when patients should be referred to their physician. A “red flag” referral within 4 weeks was recommended when SBP was >140 mm Hg or DBP >90 mm Hg (for subjects 160 mm Hg or >90 mm Hg (≥80 years) in undetected individuals, or >130 mm Hg or >80 mm Hg (140 mm Hg or >80 mm Hg (≥65 years) in treated patients. BP was measured in 187 individuals (86 with known hypertension, mean [±SD] age 62 ± 15 years, 64% female, and 101 without known hypertension, 47 ± 16 years, 75% female) from 17 community pharmacies. In patients with hypertension, poorly controlled BP was detected in 55% (n = 47) and were referred. A total of 16/101 subjects without a history of hypertension were referred to their physician because of uncontrolled BP. Structured BP testing in pharmacies identified a significant number of subjects with undetected/undiagnosed hypertension and patients with poorly controlled BP. Community pharmacists could play a significant role in collaboration with physicians to improve the management of hypertension

A Path Algorithm for Constrained Estimation

Many least squares problems involve affine equality and inequality constraints. Although there are variety of methods for solving such problems, most statisticians find constrained estimation challenging. The current paper proposes a new path following algorithm for quadratic programming based on exact penalization. Similar penalties arise in $l_1$ regularization in model selection. Classical penalty methods solve a sequence of unconstrained problems that put greater and greater stress on meeting the constraints. In the limit as the penalty constant tends to $\infty$, one recovers the constrained solution. In the exact penalty method, squared penalties are replaced by absolute value penalties, and the solution is recovered for a finite value of the penalty constant. The exact path following method starts at the unconstrained solution and follows the solution path as the penalty constant increases. In the process, the solution path hits, slides along, and exits from the various constraints. Path following in lasso penalized regression, in contrast, starts with a large value of the penalty constant and works its way downward. In both settings, inspection of the entire solution path is revealing. Just as with the lasso and generalized lasso, it is possible to plot the effective degrees of freedom along the solution path. For a strictly convex quadratic program, the exact penalty algorithm can be framed entirely in terms of the sweep operator of regression analysis. A few well chosen examples illustrate the mechanics and potential of path following.Comment: 26 pages, 5 figure