26 research outputs found
LLaMA-Reviewer: Advancing Code Review Automation with Large Language Models through Parameter-Efficient Fine-Tuning (Practical Experience Report)
The automation of code review activities, a long-standing pursuit in software
engineering, has been primarily addressed by numerous domain-specific
pre-trained models. Despite their success, these models frequently demand
extensive resources for pre-training from scratch. In contrast, Large Language
Models (LLMs) provide an intriguing alternative, given their remarkable
capabilities when supplemented with domain-specific knowledge. However, their
potential for automating code review tasks remains largely unexplored.
In response to this research gap, we present LLaMA-Reviewer, an innovative
framework that leverages the capabilities of LLaMA, a popular LLM, in the realm
of code review. Mindful of resource constraints, this framework employs
parameter-efficient fine-tuning (PEFT) methods, delivering high performance
while using less than 1% of trainable parameters.
An extensive evaluation of LLaMA-Reviewer is conducted on two diverse,
publicly available datasets. Notably, even with the smallest LLaMA base model
consisting of 6.7B parameters and a limited number of tuning epochs,
LLaMA-Reviewer equals the performance of existing code-review-focused models.
The ablation experiments provide insights into the influence of various
fine-tuning process components, including input representation, instruction
tuning, and different PEFT methods. To foster continuous progress in this
field, the code and all PEFT-weight plugins have been made open-source.Comment: Accepted to the 34th IEEE International Symposium on Software
Reliability Engineering (ISSRE 2023
Outlier-Detection Based Robust Information Fusion for Networked Systems
We consider state estimation for networked systems where measurements from
sensor nodes are contaminated by outliers. A new hierarchical measurement model
is formulated for outlier detection by integrating the outlier-free measurement
model with a binary indicator variable. The binary indicator variable, which is
assigned a beta-Bernoulli prior, is utilized to characterize if the sensor's
measurement is nominal or an outlier. Based on the proposed outlier-detection
measurement model, both centralized and decentralized information fusion
filters are developed. Specifically, in the centralized approach, all
measurements are sent to a fusion center where the state and outlier indicators
are jointly estimated by employing the mean-field variational Bayesian
inference in an iterative manner. In the decentralized approach, however, every
node shares its information, including the prior and likelihood, only with its
neighbors based on a hybrid consensus strategy. Then each node independently
performs the estimation task based on its own and shared information. In
addition, an approximation distributed solution is proposed to reduce the local
computational complexity and communication overhead. Simulation results reveal
that the proposed algorithms are effective in dealing with outliers compared
with several recent robust solutions
Spatially Adaptive Self-Supervised Learning for Real-World Image Denoising
Significant progress has been made in self-supervised image denoising (SSID)
in the recent few years. However, most methods focus on dealing with spatially
independent noise, and they have little practicality on real-world sRGB images
with spatially correlated noise. Although pixel-shuffle downsampling has been
suggested for breaking the noise correlation, it breaks the original
information of images, which limits the denoising performance. In this paper,
we propose a novel perspective to solve this problem, i.e., seeking for
spatially adaptive supervision for real-world sRGB image denoising.
Specifically, we take into account the respective characteristics of flat and
textured regions in noisy images, and construct supervisions for them
separately. For flat areas, the supervision can be safely derived from
non-adjacent pixels, which are much far from the current pixel for excluding
the influence of the noise-correlated ones. And we extend the blind-spot
network to a blind-neighborhood network (BNN) for providing supervision on flat
areas. For textured regions, the supervision has to be closely related to the
content of adjacent pixels. And we present a locally aware network (LAN) to
meet the requirement, while LAN itself is selectively supervised with the
output of BNN. Combining these two supervisions, a denoising network (e.g.,
U-Net) can be well-trained. Extensive experiments show that our method performs
favorably against state-of-the-art SSID methods on real-world sRGB photographs.
The code is available at https://github.com/nagejacob/SpatiallyAdaptiveSSID.Comment: CVPR 2023 Camera Read
Proteomics study of changes in soybean lines resistant and sensitive to Phytophthora sojae
<p>Abstract</p> <p>Background</p> <p><it>Phytophthora sojae </it>causes soybean root and stem rot, resulting in an annual loss of 1-2 billion US dollars in soybean production worldwide. A proteomic technique was used to determine the effects on soybean hypocotyls of infection with <it>P. sojae</it>.</p> <p>Results</p> <p>In the present study, 46 differentially expressed proteins were identified in soybean hypocotyls infected with <it>P. sojae</it>, using two-dimensional electrophoresis and matrix-assisted laser desorption/ionization tandem time of flight (MALDI-TOF/TOF). The expression levels of 26 proteins were significantly affected at various time points in the tolerant soybean line, Yudou25, (12 up-regulated and 14 down-regulated). In contrast, in the sensitive soybean line, NG6255, only 20 proteins were significantly affected (11 up-regulated and 9 down-regulated). Among these proteins, 26% were related to energy regulation, 15% to protein destination and storage, 11% to defense against disease, 11% to metabolism, 9% to protein synthesis, 4% to secondary metabolism, and 24% were of unknown function.</p> <p>Conclusion</p> <p>Our study provides important information on the use of proteomic methods for studying protein regulation during plant-oomycete interactions.</p
Science Classes in English at a Super Science High School: Biology Classes on Cells and Chemistry Classes on Chemical Bonding
Ⅲ大学以外の授業実践研究departmental bulletin pape
Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study
Summary
Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally.
Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies
have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of
the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income
countries globally, and identified factors associated with mortality.
Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to
hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis,
exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a
minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical
status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary
intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause,
in-hospital mortality for all conditions combined and each condition individually, stratified by country income status.
We did a complete case analysis.
Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital
diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal
malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome
countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male.
Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3).
Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income
countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups).
Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome
countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries;
p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients
combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11],
p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20
[1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention
(ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety
checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed
(ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of
parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65
[0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality.
Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome,
middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will
be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger
than 5 years by 2030
A bio-based sport community in Brettenzone
As a part of the General Extension Plan of Amsterdam, the Brettenzone was supposed to be a green recreational area and one of the green ‘wedges’ bringing nature and air into the city. The Brettenzone area divides the Amsterdam West into two parts, business area and harbor district in north and residential area in south, and the large greenery space of Brettenzone result in little communication between these two parts. The lack of public program and public space limit people's intention to enter this area, which obstruct the development of Brettenzone area. The goal of the project is in order to create meeting space for neighborhood while not having sacrificed, but rather extended the green space, attracting people from neighborhoods to enter this isolated space cover by greenery. Natural material and green roof will applied in the project to help the building to merge in the environment full with greenery.Architecture, Urbanism and Building Science