Programming by Example Made Easy

Programming by example (PBE) is an emerging programming paradigm that automatically synthesizes programs specified by user-provided input-output examples. Despite the convenience for end-users, implementing PBE tools often requires strong expertise in programming language and synthesis algorithms. Such a level of knowledge is uncommon among software developers. It greatly limits the broad adoption of PBE by the industry. To facilitate the adoption of PBE techniques, we propose a PBE framework called Bee, which leverages an "entity-action" model based on relational tables to ease PBE development for a wide but restrained range of domains. Implementing PBE tools with Bee only requires adapting domain-specific data entities and user actions to tables, with no need to design a domain-specific language or an efficient synthesis algorithm. The synthesis algorithm of Bee exploits bidirectional searching and constraint-solving techniques to address the challenge of value computation nested in table transformation. We evaluated Bee's effectiveness on 64 PBE tasks from three different domains and usability with a human study of 12 participants. Evaluation results show that Bee is easier to learn and use than the state-of-the-art PBE framework, and the bidirectional algorithm achieves comparable performance to domain-specifically optimized synthesizers.Comment: Accepted by ACM Transactions on Software Engineering and Methodolog

Identifying and Mitigating Vulnerabilities in LLM-Integrated Applications

Large language models (LLMs) are increasingly deployed as the service backend for LLM-integrated applications such as code completion and AI-powered search. LLM-integrated applications serve as middleware to refine users' queries with domain-specific knowledge to better inform LLMs and enhance the responses. Despite numerous opportunities and benefits, LLM-integrated applications also introduce new attack surfaces. Understanding, minimizing, and eliminating these emerging attack surfaces is a new area of research. In this work, we consider a setup where the user and LLM interact via an LLM-integrated application in the middle. We focus on the communication rounds that begin with user's queries and end with LLM-integrated application returning responses to the queries, powered by LLMs at the service backend. For this query-response protocol, we identify potential vulnerabilities that can originate from the malicious application developer or from an outsider threat initiator that is able to control the database access, manipulate and poison data that are high-risk for the user. Successful exploits of the identified vulnerabilities result in the users receiving responses tailored to the intent of a threat initiator. We assess such threats against LLM-integrated applications empowered by OpenAI GPT-3.5 and GPT-4. Our empirical results show that the threats can effectively bypass the restrictions and moderation policies of OpenAI, resulting in users receiving responses that contain bias, toxic content, privacy risk, and disinformation. To mitigate those threats, we identify and define four key properties, namely integrity, source identification, attack detectability, and utility preservation, that need to be satisfied by a safe LLM-integrated application. Based on these properties, we develop a lightweight, threat-agnostic defense that mitigates both insider and outsider threats

Joint Location, Bandwidth and Power Optimization for THz-enabled UAV Communications

In this paper, the problem of unmanned aerial vehicle (UAV) deployment, power allocation, and bandwidth allocation is investigated for a UAV-assisted wireless system operating at terahertz (THz) frequencies. In the studied model, one UAV can service ground users using the THz frequency band. However, the highly uncertain THz channel will introduce new challenges to the UAV location, user power, and bandwidth allocation optimization problems. Therefore, it is necessary to design a novel framework to deploy UAVs in the THz wireless systems. This problem is formally posed as an optimization problem whose goal is to minimize the total delays of the uplink and downlink transmissions between the UAV and the ground users by jointly optimizing the deployment of the UAV, the transmit power and the bandwidth of each user. The communication delay is crucial for emergency communications. To tackle this nonconvex delay minimization problem, an alternating algorithm is proposed while iteratively solving three subproblems: location optimization subproblem, power control subproblem, and bandwidth allocation subproblem. Simulation results show that the proposed algorithm can reduce the transmission delay by up to $59.3\%$, $49.8\%$ and $75.5\%$ respectively compared to baseline algorithms that optimize only UAV location, bandwidth allocation or transmit power control.Comment: 5 pages IEEE Communications Letter

Ultralight and porous cellulose nanofibers/polyethyleneimine composite aerogels with exceptional performance for selective anionic dye adsorption

It is significant to develop new adsorbents with excellent adsorption performance and convenient operation ability for removing pollutants from wastewater owing to the growing environmental problems. In this paper, a novel ultralight aerogel-based adsorbent with highly porous structure and good mechanical integrity was fabricated based on the interaction of amine groups on polyethyleneimine (PEI) and hydroxyl groups on cellulose nanofibers (CNF), with epichlorohydrin (ECH) serving as a crosslinker. The obtained CNF/PEI aerogel showed excellent water stability in harsh conditions, fast water-activated shape recovery, and ultra-fast water transport. The adsorption capacity for methyl orange (MO) in batch can reach to1226 mg g−1 at pH 6. Furthermore, the membrane also exhibited excellent selective adsorption and filtration, and separation performance. Therefore, this paper presents a new strategy to prepare low-cost and highly efficient adsorbents to remove organic dyes from wastewater for potential practical applications.</p

Identification and Characterization of New Resistance-Conferring SGI1s (Salmonella Genomic Island 1) in Proteus mirabilis

Salmonella genomic island 1 (SGI1) is a resistance-conferring chromosomal genomic island that contains an antibiotic resistance gene cluster. The international spread of SGI1-containing strains drew attention to the role of genomic islands in the dissemination of antibiotic resistance genes in Salmonella and other Gram-negative bacteria. In this study, five SGI1 variants conferring multidrug and heavy metal resistance were identified and characterized in Proteus mirabilis strains: SGI1-PmCAU, SGI1-PmABB, SGI1-PmJN16, SGI1-PmJN40, and SGI1-PmJN48. The genetic structures of SGI1-PmCAU and SGI1-PmABB were identical to previously reported SGI1s, while structural analysis showed that SGI1-PmJN16, SGI1-PmJN40, and SGI1-PmJN48 are new SGI1 variants. SGI1-PmJN16 is derived from SGI1-Z with the MDR region containing a new gene cassette array dfrA12-orfF-aadA2-qacEΔ1-sul1-chrA-orf1. SGI1-PmJN40 has an unprecedented structure that contains two right direct repeat sequences separated by a transcriptional regulator-rich DNA fragment, and is predicted to form two different extrachromosomal mobilizable DNA circles for dissemination. SGI1-PmJN48 lacks a common ORF S044, and its right junction region exhibits a unique genetic organization due to the reverse integration of a P. mirabilis chromosomal gene cluster and the insertion of part of a P. mirabilis plasmid, making it the largest known SGI1 to date (189.1 kb). Further mobility functional analysis suggested that these SGIs can be excised from the chromosome for transfer between bacteria, which promotes the horizontal transfer of antibiotic and heavy metal resistance genes. The identification and characterization of the new SGI1 variants in this work suggested the diversity of SGI1 structures and their significant roles in the evolution of bacteria

Retrospective analysis of image characteristics of 76 cases of cerebral vascular fenestrations

ObjectivesThis study aims to summarize the clinical and imaging features of cerebral vascular fenestration and to explore the association between cerebral vascular fenestration and cerebral infarction and aneurysm.Materials and methodsThe computed tomography angiography (CTA), magnetic resonance angiography (MRA), and digital subtraction angiography (DSA) imaging data of 76 cases of cerebral vascular fenestration from January 2021 and December 2021 in the Yantai Yuhuangding Hospital Affiliated to Qingdao University were analyzed. The general information was described. The location, morphology, and size of cerebral vascular fenestration were described. The association between cerebral vascular fenestration and infarction and aneurysm was analyzed.ResultsAmong 76 patients, a total of 80 fenestrations were detected (two patients had three fenestrations), and basilar artery fenestration was the most common (28/80). The fenestration &lt;5 mm was 43/80, 5–10 mm was 12/80, and ≥10 mm was 25/80. Moreover, 19 patients had other vascular diseases: 10 with aneurysms, 5 with moyamoya diseases, and 4 with cerebral artery dissections. Except for one aneurysm at the site of the fenestration, other aneurysms were separate from the fenestrations. In addition, 37 patients had cerebral infarctions, of which 16 had cerebral infarctions in the blood supply area of the arterial fenestration. Among these 16 patients, there was more cerebral infarction in posterior circulation than in anterior circulation. However, no statistically significant differences were detected in the risk factors between the fenestration-relevant cerebral infarctions group and the non-fenestration-relevant cerebral infarctions group.ConclusionIn our study, cerebral vascular fenestration occurred most frequently in the basilar artery and may be combined with other vascular diseases. Fenestration in posterior circulation may be related to cerebrovascular diseases. Nonetheless, no clear clinical relevance was observed between fenestration and cerebral infarction. Also, we did not find a definite association between fenestration and aneurysm. For fenestration patients with cerebral infarctions, long-term antiplatelet and statin therapy may be safe and effective

Can tourists become disciples? The formation and mechanism of place conversion in traditional Chinese villages

Place attachment has been extensively studied in the field of tourism. However, it is important to recognize that place attachment alone may not fully capture the emotional expression of tourists’ spiritual beliefs and their sense of belonging to a destination. Therefore, a more comprehensive attachment theory is needed to encompass higher dimensions. This article focuses on the ancient Chinese villages of Yantou, Cangpo, and Furong from a tourist perspective, and introduces genius loci in architectural phenomenology. We set out to expand the study of spiritual dimensions of place attachment on the basis of local attachment, redefining tourists’ place connection and putting forward the new concept of place conversion. A qualitative analysis of online text using Rooting theory was conducted to condense 22 categories into 6 main categories and establish a model. The study shows that the mechanism of place conversion is composed of situational perception (place perception and place identity), physical and mental immersion (spatio-temporal immersion and place conversion), and behavioral willingness (tourists intention and conversion behavior). The study has implications for the conservation and development of traditional villages and future research on the spiritual experiences of tourists