Learning to Prune: Speeding up Repeated Computations

It is common to encounter situations where one must solve a sequence of similar computational problems. Running a standard algorithm with worst-case runtime guarantees on each instance will fail to take advantage of valuable structure shared across the problem instances. For example, when a commuter drives from work to home, there are typically only a handful of routes that will ever be the shortest path. A naive algorithm that does not exploit this common structure may spend most of its time checking roads that will never be in the shortest path. More generally, we can often ignore large swaths of the search space that will likely never contain an optimal solution. We present an algorithm that learns to maximally prune the search space on repeated computations, thereby reducing runtime while provably outputting the correct solution each period with high probability. Our algorithm employs a simple explore-exploit technique resembling those used in online algorithms, though our setting is quite different. We prove that, with respect to our model of pruning search spaces, our approach is optimal up to constant factors. Finally, we illustrate the applicability of our model and algorithm to three classic problems: shortest-path routing, string search, and linear programming. We present experiments confirming that our simple algorithm is effective at significantly reducing the runtime of solving repeated computations

NaijaCoder: Participatory Design for Early Algorithms Education in the Global South

The majority of Nigerian high schoolers have little to no exposure to the basics of algorithms and programming. We believe this trajectory should change as programming offers these students, especially those from indigent backgrounds, an opportunity to learn profitable skills and ignite their passions for problem-solving and critical thinking. NaijaCoder is an organization that is dedicated to organizing a free, intensive summer program in Nigeria to teach the basics of algorithms and computer programming to high schoolers. However, the adoption of computer science curriculum has been especially challenging in countries in the global south that face unique challenges -- such as unstable power supply, internet service, and price volatility. We design a curriculum that is more conducive to the local environment while incorporating rigorous thinking and preparation. Using basic survey designs, we elicit feedback, from the students, designed to further improve and iterate on our curriculum.Comment: Accepted for presentation at the Technical Symposium on Computer Science Education (SIGCSE TS) 202

Development of siRNA-probes for studying intracellular trafficking of siRNA nanoparticles

One important barrier facing the delivery of short interfering RNAs (siRNAs) via synthetic nanoparticles is the rate of nanoparticle disassembly. However, our ability to optimize the release kinetics of siRNAs from nanoparticles for maximum efficacy is limited by the lack of methods to track their intracellular disassembly. Towards this end, we describe the design of two different siRNA-based fluorescent probes whose fluorescence emission changes in response to the assembly state of the nanoparticle. The first probe design involves a redox-sensitive fluorescence-quenched probe that fluoresces only when the nanoparticle is disassembled in a reductive environment. The second probe design is based on a FRET-labeled siRNA pair that fluoresces due to the proximity of the siRNA pair when the nanoparticle is intact. In both approaches, the delivery vehicle need not be labeled. The utility of these probes was investigated with a lipidoid nanoparticle (LNP) as proof-of-concept in both extracellular and intracellular environments. Fluorescence kinetic data from both probes were fit to a two-phase release and decay curve and subsequently quantified to give intracellular disassembly rate constants. Quantitative analysis revealed that the rate constant of siRNA release measured via the fluorescence-quenched probe was almost identical to the rate constant for nanoparticle disassembly measured via the FRET-labeled probes. Furthermore, these probes were utilized to determine subcellular localization of LNPs with the use of automated high-resolution microscopy as they undergo dissociation. Interestingly, this work shows that large amounts of siRNA remain inside vesicular compartments. Altogether, we have developed new siRNA probes that can be utilized with multiple nanocarriers for quantitative and qualitative analysis of nanoparticle dissociation that may serve as a design tool for future delivery systems.National Institutes of Health (U.S.) (Grant R37-EB000244)National Institutes of Health (U.S.) (Grant R01-CA132091)National Institutes of Health (U.S.) (Grant R01-CA132091)National Institutes of Health (U.S.) (Postdoctoral Fellowship

Privately Estimating a Gaussian: Efficient, Robust and Optimal

In this work, we give efficient algorithms for privately estimating a Gaussian distribution in both pure and approximate differential privacy (DP) models with optimal dependence on the dimension in the sample complexity. In the pure DP setting, we give an efficient algorithm that estimates an unknown $d$-dimensional Gaussian distribution up to an arbitrary tiny total variation error using $\widetilde{O}(d^2 \log \kappa)$ samples while tolerating a constant fraction of adversarial outliers. Here, $\kappa$ is the condition number of the target covariance matrix. The sample bound matches best non-private estimators in the dependence on the dimension (up to a polylogarithmic factor). We prove a new lower bound on differentially private covariance estimation to show that the dependence on the condition number $\kappa$ in the above sample bound is also tight. Prior to our work, only identifiability results (yielding inefficient super-polynomial time algorithms) were known for the problem. In the approximate DP setting, we give an efficient algorithm to estimate an unknown Gaussian distribution up to an arbitrarily tiny total variation error using $\widetilde{O}(d^2)$ samples while tolerating a constant fraction of adversarial outliers. Prior to our work, all efficient approximate DP algorithms incurred a super-quadratic sample cost or were not outlier-robust. For the special case of mean estimation, our algorithm achieves the optimal sample complexity of $\widetilde O(d)$, improving on a $\widetilde O(d^{1.5})$ bound from prior work. Our pure DP algorithm relies on a recursive private preconditioning subroutine that utilizes the recent work on private mean estimation [Hopkins et al., 2022]. Our approximate DP algorithms are based on a substantial upgrade of the method of stabilizing convex relaxations introduced in [Kothari et al., 2022]

Hot Red Pepper (Capsicum annum L.) Meal Enhanced the Immunity, Performance and Economy of Broilers Fed in Phases

Feeding of poultry in phases had been advocated to prevent wastage of nutrients, resources, and environmental pollution; and for optimal performance at every stage of production. The possibility of using organic materials like spices such as hot red pepper meal as feed additive to enhance performance is hereby tested. The effect of dietary Dried Hot Red Pepper-DHRP (Capsicum annum) meal on the performance, haematology, and carcass traits of broilers fed in three phases were evaluated. In a CRD, 240 day-old broiler chicks were allotted to four experimental diets or treatments at the pre-starter (0 - 3rd weeks), starter (4 – 6th weeks) and finisher (7th week) phases for 7 weeks on deep litter poultry house at 20 chicks per replicate of three. Four experimental diets were formulated for each of the growth phases with 0.1, 0.2 and 0.3 % DHRP meal in diets 2, 3 and 4 respectively; while diet 1 without DHRP meal served as the control. The performance at the end of 7th week showed that feed intake and daily Body Weight Gain (BWG) for birds fed diets with DHRP meal were significantly (p < 0.05) higher than what obtained for those on control diet. The least Feed conversion Ratio-FCR (2.06) and least cost of feed intake per kg BWG (₦273.6) were obtained for birds fed diets with 0.2% DHRP meal. DHRP meal in broilers diet significantly increased the BWG and decreased the FCR and cost of feed intake. The leucocytes of broilers fed diets with DHRP meal beyond 0.1% level were elevated significantly. Relative broilers’ carcass cut and internal organs weights were not adversely affected by DHRP meal-based diets. Inclusion of up to 0.2% hot red pepper meal in broilers diet improved their performance at a lower cost; had no adverse effect on their carcass traits and haematology but elevated the leucocytes cell count as a potential immunity booster. Keywords: Hot red pepper (Capsicum annum), Performance, Broiler, Haematology, Carcas

Measuring Public Utilization Perception Potential of Unmanned Aircraft Systems

The integration of Unmanned Aircraft Systems (UAS) into the National Air Space (NAS) in recent times has been met by mixed public responses. The paper establishes four constructs each of which encapsulates multiple backgrounds and concerns of the stakeholders: functional knowledge, utilization trust, operational integration support, and safety risk-benefits. The paper hypothesizes that these constructs can serve as underlying components for a research instrument namely, the Public Utilization Perception Potential (PUPP) which can be used to assess the opinions of the public on UAS integration into NAS. Responses from the public on items in a beta-tested survey instrument were analyzed for construct validity and reliability using Principal Axis Factoring (PAF). Four factors that suggest constructs underlying PUPP instrument were derived. Using Structural Equation Model (SEM) approach, a hypothesized measurement model of PUPP was further validated and the final measurement model showed good fit of the observed data based on the RMSEA goodness-of-fit index (0.034). The paper further assessed the strength of relationships between the underlying constructs of PUPP. The results suggest that approximately 65% and 27% of all respondents had partial and no knowledge, respectively, about UAS integration into the NAS. There was a statistically significant difference in the mean scores on safety-risk benefits on UAS among gender. Males were found to be more likely to patronize unmanned commercial passenger services compared to females. The results indicated a statistically significant difference in UAS knowledge and perceptions across educational levels. It was rather counter-intuitive as respondents with lower educational levels were found to be more knowledgeable about UAS compared to those of higher levels based on the results of this study. Investments in information resources and training by industry, government and academia may be helpful to improve UAS knowledge and perceptions among the public if any commercial utilization as a transport mode will be feasible. Future studies will replicate the study in countries other than the United States