Search

Large language models such as ChatGPT have been shown to excel in solving complex math problems. However, they cannot solve basic arithmetic problems such as 758*639 = 484,362. This makes us ponder if LLMs have been trained to solve math and science problems in the right way. When a student learns math at school, she or he starts with arithmetic, then moves to word problems, polynomials, and calculus. Each skill she or he acquires will be used in the next stage to solve more advanced problems. In this paper we propose Scaffolding Learning for LLMs, which imitates how a student learns a subject in a step-by-step manner. For example, we first train an LLM to perform highly specific operations such as multiplication and division, and then apply such "skills" in a more generic task such as solving word problems. This is related to Curriculum Training, which trains a model on tasks following a specific order, such as training on easy tasks first and then gradually increases the difficulty. Our proposed approach goes from specific tasks to generic ones, which can be considered as a special case of Curriculum Training. Our empirical studies show that when an LLM has "mastered" a specific skill, only a small amount of training is required to teach it to apply the skill to a more generic application. [ABSTRACT FROM AUTHOR]

A Ka-band compact single layer substrate integrated waveguide monopulse slot array antenna for the application of monopulse tracking system is designed, fabricated and measured. The feeding network as well as the monopulse comparator and the subarrays is integrated on the same dielectric with the size of 140 mm x 130 mm. The bandwidth ([S.sub.11] < - 10 dB) of the antenna is 7.39 % with an operating frequency range of 30.80 GHz-33.14 GHz. The maximum gain at 31.5 GHz is 18.74 dB and the maximum null depth is -46.3 dB. The sum- and difference patterns of three planes: H-plane, E-plane and diagonal plane are measured and presented. Index Terms--Difference pattern, monopulse antenna, null depth, substrate integrated waveguide, sum pattern.

The World Wide Web has become the most important information source for most of us. Unfortunately, there is no guarantee for the correctness of information on the Web. Moreover, different websites often provide conflicting information on a subject, such as different specifications for the same product. In this paper, we propose a new problem, called Veracity, i.e., conformity to truth, which studies how to find true facts from a large amount of conflicting information on many subjects that is provided by various websites. We design a general framework for the Veracity problem and invent an algorithm, called TRUTHFINDER, which utilizes the relationships between websites and their information, i.e., a website is trustworthy if it provides many pieces of true information, and a piece of information is likely to be true if it is provided by many trustworthy websites. An iterative method is used to infer the trustworthiness of websites and the correctness of information from each other. Our experiments show that TRUTHFINDER successfully finds true facts among conflicting information and identifies trustworthy websites better than the popular search engines. Index Terms--Data quality, Web mining, link analysis.

In this paper, two types of half mode substrate integrated waveguide 180[degrees] couplers are proposed, the phase-shifting structures of which are composed of metallic via fins or etched air slots. Each coupler maintains the good performance of the substrate integrated waveguide coupler with a half reduction in size and a 180[degrees] phase difference between through and coupling ports. Prototypes working in the C-, X-, Ku-, and Ka-bands are designed and fabricated using the standard printed circuit board process. The consistency between the measured data and simulated results shows that the proposed couplers have the merits of low profile and good performance. Index Terms--Half mode substrate integrated waveguide, 180[degrees] directional coupler, substrate integrated waveguide.

Relational databases are the most popular repository for structured data, and is thus one of the richest sources of knowledge in the world. In a relational database, multiple relations are linked together via entity-relationship links. Multirelational classification is the procedure of building a classifier based on information stored in multiple relations and making predictions with it. Existing approaches of Inductive Logic Programming (recently, also known as Relational Mining) have proven effective with high accuracy in multirelational classification. Unfortunately, most of them suffer from scalability problems with regard to the number of relations in databases. In this paper, we propose a new approach, called CrossMine, which includes a set of novel and powerful methods for multirelational classification, including 1) tuple ID propagation, an efficient and flexible method for virtually joining relations, which enables convenient search among different relations, 2) new definitions for predicates and decision-tree nodes, which involve aggregated information to provide essential statistics for classification, and 3) a selective sampling method for improving scalability with regard to the number of tuples. Based on these techniques, we propose two scalable and accurate methods for multirelational classification: CrossMine-Rule, a rule-based method and CrossMine-Tree, a decision-tree-based method. Our comprehensive experiments on both real and synthetic data sets demonstrate the high scalability and accuracy of the CrossMine approach. Index Terms--Data mining, classification, relational databases.

Metoclopramide (MCP) can effectively alleviate motion sickness-caused nausea and vomiting. Nasal administration offers the greatest patient compliance. It is suitable for self-administration and offers rapid and complete absorption, no first-pass effects and high bioavailability. In the present study, a MCP nasal spray was prepared and evaluatedin vitroandin vivo.Nasal cilia toxicity of Bufo toads was used to screen the preservative types and concentrations. Rabbit nasal mucosa was used to evaluate the mucosa permeability of different MCP nasal sprays with different penetration enhancers and preservative. A three-period crossover trial was then carried out in beagle dogs with three different MCP dosage forms: nasal sprays, oral tablets and intramuscular (IM) solution. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) was performed to measure dog plasma MCP, and pharmacokinetic parameters were calculated. The results of ciliatoxicity and permeation study showed that 0.03% methyl paraben lacking penetration enhancers was optimal. Compared to control IM, the bioavailability of oral tablets of MCP was 24.9%, while that of nasal spray was 62.3%. Meanwhile time-to-maximal plasma concentration (Tmax) of nasal spray was significantly shorter than that of oral tablets. In conclusion, MCP nasal spray prepared here is safe with minimal ciliatoxicity, rapid onset and high relative bioavailability. [ABSTRACT FROM PUBLISHER]

Abstract: The direct one‐pot synthesis of terminal propargylic amines from trimethylsilylacetylene (TMS–acetylene) with variety of amines and aldehydes using anhydrous CuSO4 as a catalyst in absence of fluoride has been developed. This methodology is compatible with a variety of functional groups, and moderate to excellent yields are successfully achieved. [ABSTRACT FROM AUTHOR]