Arctic Ocean Freshwater in CMIP6 Coupled Models

In this study we assessed the representation of the sea surface salinity (SSS) and liquid freshwater content (LFWC) of the Arctic Ocean in the historical simulation of 31 CMIP6 models with comparison to 39 Coupled Model Intercomparison Project phase 5 (CMIP5) models, and investigated the projected changes in Arctic liquid and solid freshwater content and freshwater budget in scenarios with two different shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5). No significant improvement was found in the SSS and LFWC simulation from CMIP5 to CMIP6, given the large model spreads in both CMIP phases. The overestimation of LFWC continues to be a common bias in CMIP6. In the historical simulation, the multi-model mean river runoff, net precipitation, Bering Strait and Barents Sea Opening (BSO) freshwater transports are 2,928 ± 1,068, 1,839 ± 3,424, 2,538 ± 1,009, and −636 ± 553 km3/year, respectively. In the last decade of the 21st century, CMIP6 MMM projects these budget terms to rise to 4,346 ± 1,484 km3/year (3,678 ± 1,255 km3/year), 3,866 ± 2,935 km3/year (3,145 ± 2,651 km3/year), 2,631 ± 1,119 km3/year (2,649 ± 1,141 km3/year) and 1,033 ± 1,496 km3/year (449 ± 1,222 km3/year) under SSP5-8.5 (SSP2-4.5). Arctic sea ice is expected to continue declining in the future, and sea ice meltwater flux is likely to decrease to about zero in the mid-21st century under both SSP2-4.5 and SSP5-8.5 scenarios. Liquid freshwater exiting Fram and Davis straits will be higher in the future, and the Fram Strait export will remain larger. The Arctic Ocean is projected to hold a total of 160,300 ± 62,330 km3 (141,590 ± 50,310 km3) liquid freshwater under SSP5-8.5 (SSP2-4.5) by 2100, about 60% (40%) more than its historical climatology

Arctic Ocean Simulations in the CMIP6 Ocean Model Intercomparison Project (OMIP)

oai:publications.copernicus.org:gmdd107357Arctic Ocean simulations in 19 global ocean-sea ice models participating in the Ocean Model Intercomparison Project (OMIP) of the CMIP6 are evaluated in this paper. Our results indicate that no significant improvements were achieved in the Arctic Ocean simulations from the previous Coordinated Ocean-ice Reference Experiments phase II (CORE-II) to the current OMIP. Large model biases and inter-model spread exist in the simulated mean state of the halocline and Atlantic Water layer in the OMIP models. Most of the OMIP models suffer from too thick and deep Atlantic Water layer, too deep halocline base, and large fresh biases in the halocline. The OMIP models largely agree on the inter-annual and decadal variability of the Arctic Ocean freshwater content and volume/heat/freshwater transports through the Arctic Ocean gateways. The models can reproduce observed changes in volume, heat and freshwater transports through the gateways except for the Bering Strait. Overall, the performance of the Arctic Ocean simulations is similar between the CORE2-forced OMIP-1 and JRA55-do-forced OMIP-2.</p

Arctic Ocean Amplification in a warming climate in CMIP6 models

Arctic near-surface air temperature warms much faster than the global average, a phenomenon known as Arctic Amplification. The change of the underlying Arctic Ocean could influence climate through its interaction with sea ice, atmosphere, and the global ocean, but it is less well understood. Here, we show that the upper 2000 m of the Arctic Ocean warms at 2.3 times the global mean rate within this depth range averaged over the 21st century in the Coupled Model Intercomparison Project Phase 6 Shared Socioeconomic Pathway 585 scenario. We call this phenomenon the “Arctic Ocean Amplification.” The amplified Arctic Ocean warming can be attributed to a substantial increase in poleward ocean heat transport, which will continue outweighing sea surface heat loss in the future. Arctic Amplification of both the atmosphere and ocean indicates that the Arctic as a whole is one of Earth’s regions most susceptible to climate change

Halo: Estimation and Reduction of Hallucinations in Open-Source Weak Large Language Models

Large Language Models (LLMs) have revolutionized Natural Language Processing (NLP). Although convenient for research and practical applications, open-source LLMs with fewer parameters often suffer from severe hallucinations compared to their larger counterparts. This paper focuses on measuring and reducing hallucinations in BLOOM 7B, a representative of such weaker open-source LLMs that are publicly available for research and commercial applications. We introduce HaloCheck, a lightweight BlackBox knowledge-free framework designed to quantify the severity of hallucinations in LLMs. Additionally, we explore techniques like knowledge injection and teacher-student approaches to alleviate hallucinations in low-parameter LLMs. Our experiments effectively demonstrate the reduction of hallucinations in challenging domains for these LLMs

Future Arctic Climate Change in CMIP6 Strikingly Intensified by NEMO‐Family Climate Models

Climate change in the Arctic has substantial impacts on human life and ecosystems both within and beyond the Arctic. Our analysis of CMIP6 simulations shows that some climate models project much larger Arctic climate change than other models, including changes in sea ice, ocean mixed layer, air-sea heat flux, and surface air temperature in wintertime. In particular, dramatic enhancement of Arctic Ocean convection down to a few hundred meters is projected in these models but not in others. Interestingly, these models employ the same ocean model family (NEMO) while the choice of models for the atmosphere and sea ice varies. The magnitude of Arctic climate change is proportional to the strength of the increase in poleward ocean heat transport, which is considerably higher in this group of models. Establishing the plausibility of this group of models with high Arctic climate sensitivity to anthropogenic forcing is imperative given the implied ramifications

LMTuner: An user-friendly and highly-integrable Training Framework for fine-tuning Large Language Models

With the burgeoning development in the realm of large language models (LLMs), the demand for efficient incremental training tailored to specific industries and domains continues to increase. Currently, the predominantly employed frameworks lack modular design, it often takes a lot of coding work to kickstart the training of LLM. To address this, we present "LMTuner", a highly usable, integrable, and scalable system for training LLMs expeditiously and with minimal user-input. LMTuner comprises three main modules - the Interaction, Training, and Inference Modules. We advocate that LMTuner's usability and integrality alleviate the complexities in training large language models. Remarkably, even a novice user could commence training large language models within five minutes. Furthermore, it integrates DeepSpeed frameworks and supports Efficient Fine-Tuning methodologies like Low Rank Adaptation (LoRA), Quantized LoRA (QLoRA), etc., enabling the training of language models scaling from 300M to a whopping 130B parameters using a single server. The LMTuner's homepage (https://wengsyx.github.io/LMTuner/)and screencast video (https://youtu.be/nsXmWOmN3rE) are now publicly available

Formal Proof of Relative Strengths of Security between ECK2007 Model and other Proof Models for Key Agreement Protocols

In 2005, Choo, Boyd & Hitchcock compared four well-known indistinguishability-based proof models for key agreement protocols, which contains the Bellare & Rogaway (1993, 1995) model, the Bellare , Pointcheval & Rogaway 2000 model and the Canetti & Krawczyk (2001) model. After that, researchers from Microsoft presented a stronger security model, called Extended Canetti-Krawczyk model (2007). In this paper, we will point out the differences between the new proof model and the four previous models, and analyze the relative strengths of security of these models. To support the implication or non-implication relation between these models, we will provide proof or counter-example

Mind the Propagation of States New Automatic Search Tool for Impossible Differentials and Impossible Polytopic Transitions (Full Version)

Impossible differentials cryptanalysis and impossible polytopic cryptanalysis are the most effective approaches to estimate the security of block ciphers. However, the previous automatic search methods of their distinguishers, impossible differentials and impossible polytopic transitions, neither consider the impact of key schedule in the single-key setting and the differential property of large S-boxes, nor apply to the block ciphers with variable rotations. Thus, unlike previous methods which focus on the propagation of the difference or $s$-difference, we redefine the impossible differentials and impossible $(s+1)$-polytopic transitions according to the propagation of state, which allow us to break through those limitations of the previous methods. Theoretically, we prove that traditional impossible differentials and impossible $(s+1)$-polytopic transitions are equivalent to part of our redefinitions, which have advantages from broader view. Technically, we renew the automatic search model and design an SAT-based tool to evaluate our redefined impossible differentials and impossible $(s+1)$-polytopic transitions efficiently. As a result, for GIFT64, we get the $6$-round impossible differentials which cannot be detected by all previous tools. For PRINTcipher, we propose the first modeling method for the key-dependent permutation and key-dependent S-box. For MISTY1, we derive 902 4-round impossible differentials by exploiting the differential property of S-boxes. For RC5, we present the first modeling method for the variable rotation and get 2.5-round impossible differentials for each version of it. More remarkable, our tool can be used to evaluate the security of given cipher against the impossible differentials, and we prove that there exists no 5-round 1 input active word and 1 output active word impossible differentials for AES-128 even consider the relations of 3-round keys. Besides, we also get the impossible $(s+1)$-polytopic transitions for PRINTcipher, GIFT64, PRESENT, and RC5, all of which can cover more rounds than their corresponding impossible differentials as far as we know

Chosen-Ciphertext Secure Fuzzy Identity-Based Key Encapsulation without ROM

We use hybrid encryption with Fuzzy Identity-Based Encryption (Fuzzy-IBE) schemes, and present the first and efficient fuzzy identity-based key encapsulation mechanism (Fuzzy-IB-KEM) schemes which are chosen-ciphertext secure (CCA) without random oracle in the selective-ID model. To achieve these goals, we consider Fuzzy-IBE schemes as consisting of separate key and data encapsulation mechanisms (KEM-DEM), and then give the definition of Fuzzy-IB-KEM. Our main idea is to enhance Sahai and Waters\u27 large universe construction (Sahai and Waters, 2005), chosen-plaintext secure (CPA) Fuzzy-IBE, by adding some redundant information to the ciphertext to make it CCA-secure

Continued spread of HIV among injecting drug users in southern Sichuan Province, China

OBJECTIVE: To estimate HIV prevalence among injecting drug users (IDUs) in a drug trafficking city in southwest Sichuan Province, China. METHODS: A total of 314 IDUs was invited to participate in the cross-sectional survey in 2004 through community outreach recruitment and peer referrals. Blood sample was taken for HIV antibody testing and a structured questionnaire was administered to collect information on socio-demographics, drug using and sexual behaviors. RESULTS: HIV prevalence among IDUs was 17.8% (56/314), about one half higher than that in previous survey in 2002 (11.3%, 43/379). Yi and other minority ethnicity (Odds ratio [OR], 3.1; 95% confidence interval [CI], 1.7–5.8; P < 0.001), and total times of sharing injecting equipments 1–9 times versus none, OR, 2.7; 95% CI 1.2–6.2; P = 0.02; and ≥10 times versus none, OR, 7.5; 95% CI, 3.2–17.7; P < 0.001) were independent risk factors for HIV infection. CONCLUSION: IDUs with high prevalence rates of HIV and equipment sharing behavior in the drug trafficking city may serve a source for further spread of HIV to other areas in China. The increasing trend of HIV epidemic among IDUs underscores the urgency of scaling up interventions