PINPOINT: Efficient and Effective Resource Isolation for Mobile Security and Privacy

Virtualization is frequently used to isolate untrusted processes and control their access to sensitive resources. However, isolation usually carries a price in terms of less resource sharing and reduced inter-process communication. In an open architecture such as Android, this price and its impact on performance, usability, and transparency must be carefully considered. Although previous efforts in developing general-purpose isolation solutions have shown that some of these negative sideeffects can be mitigated, doing so involves overcoming significant design challenges by incorporating numerous additional platform complexities not directly related to improved security. Thus, the general purpose solutions become inefficient and burdensome if the end-user has only specific security goals. In this paper, we present PINPOINT, a resource isolation strategy that forgoes general-purpose solutions in favor of a “building block” approach that addresses specific end-user security goals. PINPOINT embodies the concept of Linux Namespace lightweight isolation, but does so in the Android Framework by guiding the security designer towards isolation points that are contextually close to the resource(s) that need to be isolated. This strategy allows the rest of the Framework to function fully as intended, transparently. We demonstrate our strategy with a case study on Android System Services, and show four applications of PINPOINTed system services functioning with unmodified market apps. Our evaluation results show that practical security and privacy advantages can be gained using our approach, without inducing the problematic side-effects that other general-purpose designs must address

Thickness-shear Frequencies of an Infinite Quartz Plate with Material Property Variation Along the Thickness

Properties of the quartz crystal blank of a resonator is assumed homogeneous, uniform, and perfect in design, manufacturing, and applications. As end products, quartz crystal resonators are frequently exposed to gases and liquids which can cause surface damage and internal degradation of blanks under increasingly hostile conditions. The combination of service conditions and manufacturing process including chemical etching and polishing can inevitably modify the surface of quartz crystal blanks with changes of material properties, raising the question of what will happen to vibrations of quartz crystal resonators of thickness-shear type if such modifications to blanks are to be evaluated for sensitive applications. Such questions have been encountered in other materials and structures with property variations either on purpose or as the effect of environmental or natural processes commonly referred to as functionally graded materials, or FGMs. Analyses have been done in applications as part of studies on FGMs in structural as well as in acoustic wave device applications. A procedure based on series solutions has been developed in the evaluation of frequency changes and features in an infinite quartz crystal plate of AT-cut with the symmetric material variation pattern given in a cosine function with the findings that the vibration modes are now closely coupled. These results can be used in the evaluation of surface damage and corrosion of quartz crystal blanks of resonators in sensor applications or development of new structures of resonators.Comment: This is to be presented and published with the 2014 IEEE International Frequency Control Symposium, May 19-22, 2014, Taipei International Convention Center, Taipe

Thickness-shear Vibration Frequencies of an Infinite Plate with a Generalized Material Property Grading along the Thickness

For quartz crystal resonators of thickness-shear type, the vibration frequency and mode shapes, which are key features of resonators in circuit applications, reflect the basic material and structural properties of the quartz plate and its variation with time under various factors such as erosive gases and liquids that can cause surface and internal damages and degradation of crystal blanks. The accumulated effects eventually will change the surface conditions in terms of elastic constants and stiffness and more importantly, the gradient of such properties along the thickness. This is a typical functionally graded materials (FGM) structure and has been studied extensively for structural applications under multiple loadings such as thermal and electromagnetic fields in recent years. For acoustic wave resonators, such studies are equally important and the wave propagation in FGM structures can be used in the evaluation and assessment of performance, reliability, and life of sensors based on acoustic waves such as the quartz crystal microbalances (QCM). Now we studied the thickness-shear vibrations of FGM plates with properties of AT-cut quartz crystal varying along the thickness in a general pattern represented by a trigonometric function with both sine and cosine functions of the thickness coordinate. The solutions are obtained by using Fourier expansion of the plate deformation. We also obtained the frequency changes of the fundamental and overtone modes which are strongly coupled for the evaluation of resonator structures with property variation or design to take advantages of FGM in novel applications.Comment: Paper for the proceedings of the 2015 IEEE International Frequency Control Symposium and the European Frequency and Time Forum, Denver, CO, USA. April 12-16, 201

CrossNER: Evaluating Cross-Domain Named Entity Recognition

Cross-domain named entity recognition (NER) models are able to cope with the scarcity issue of NER samples in target domains. However, most of the existing NER benchmarks lack domain-specialized entity types or do not focus on a certain domain, leading to a less effective cross-domain evaluation. To address these obstacles, we introduce a cross-domain NER dataset (CrossNER), a fully-labeled collection of NER data spanning over five diverse domains with specialized entity categories for different domains. Additionally, we also provide a domain-related corpus since using it to continue pre-training language models (domain-adaptive pre-training) is effective for the domain adaptation. We then conduct comprehensive experiments to explore the effectiveness of leveraging different levels of the domain corpus and pre-training strategies to do domain-adaptive pre-training for the cross-domain task. Results show that focusing on the fractional corpus containing domain-specialized entities and utilizing a more challenging pre-training strategy in domain-adaptive pre-training are beneficial for the NER domain adaptation, and our proposed method can consistently outperform existing cross-domain NER baselines. Nevertheless, experiments also illustrate the challenge of this cross-domain NER task. We hope that our dataset and baselines will catalyze research in the NER domain adaptation area. The code and data are available at https://github.com/zliucr/CrossNER.Comment: Accepted in AAAI-202

A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity

This paper proposes a framework for quantitatively evaluating interactive LLMs such as ChatGPT using publicly available data sets. We carry out an extensive technical evaluation of ChatGPT using 23 data sets covering 8 different common NLP application tasks. We evaluate the multitask, multilingual and multi-modal aspects of ChatGPT based on these data sets and a newly designed multimodal dataset. We find that ChatGPT outperforms LLMs with zero-shot learning on most tasks and even outperforms fine-tuned models on some tasks. We find that it is better at understanding non-Latin script languages than generating them. It is able to generate multimodal content from textual prompts, via an intermediate code generation step. Moreover, we find that ChatGPT is 63.41% accurate on average in 10 different reasoning categories under logical reasoning, non-textual reasoning, and commonsense reasoning, hence making it an unreliable reasoner. It is, for example, better at deductive than inductive reasoning. ChatGPT suffers from hallucination problems like other LLMs and it generates more extrinsic hallucinations from its parametric memory as it does not have access to an external knowledge base. Finally, the interactive feature of ChatGPT enables human collaboration with the underlying LLM to improve its performance, i.e, 8% ROUGE-1 on summarization and 2% ChrF++ on machine translation, in a multi-turn "prompt engineering" fashion. We also release codebase for evaluation set extraction.Comment: 45 pages, AACL 202

Life history traits of low-toxicity alternative bisphenol S on Daphnia magna with short breeding cycles : A multigenerational study

Due to relatively lower toxicity, bisphenol S (BPS) has become an alternative to previously used bisphenol A. Nevertheless, the occurrence of BPS and its ecological impact have recently attracted increasing attentions because the toxicology effect of BPS with life cycle or multigenerational exposure on aquatic organisms remains questionable. Herein, Daphnia magna (D. magna) multigenerational bioassays spanning four generations (F0–F3) and single-generation recovery (F1 and F3) in clean water were used to investigate the ecotoxicology of variable chronic BPS exposure. For both assays, four kinds of life-history traits (i.e., survival, reproduction, growth and ecological behavior) were examined for each generation. After an 18-day exposure under concentration of 200 μg/L, the survival rate of D. magna was less than 15 % for the F2 generation, whereas all died for the F3 generation. With continuous exposure of four generations of D. magna at environmentally relevant concentrations of BPS (2 μg/L), inhibition of growth and development, prolonged sexual maturity, decreased offspring production and decreased swimming activity were observed for the F3 generation. In particular, it is difficult for D. magna to return to its normal level through a single-generation recovery in clean water in terms of reproductive function, ecological behavior and population health. Hence, multi-generational exposure to low concentrations of BPS can have adverse effects on population health of aquatic organisms with short breeding cycles, highlighting the necessity to assess the ecotoxicology of chronic BPS exposure for public health.publishedVersionPeer reviewe

New perspectives on microbiome and nutrient sequestration in soil aggregates during long-term grazing exclusion

15 páginas.- 5 figuras.- referencias.-Grazing exclusion alters grassland soil aggregation, microbiome composition, and biogeochemical processes. However, the long-term effects of grazing exclusion on the microbial communities and nutrient dynamics within soil aggregates remain unclear. We conducted a 36-year exclusion experiment to investigate how grazing exclusion affects the soil microbial community and the associated soil functions within soil aggregates in a semiarid grassland. Long-term (36 years) grazing exclusion induced a shift in microbial communities, especially in the 2 mm aggregates, and reduced carbon (C) sequestration potential thus revealing a negative impact of long-term GE. In contrast, 11–26 years of grazing exclusion greatly increased C sequestration and promoted nutrient cycling in soil aggregates and associated microbial functional genes. Moreover, the environmental characteristics of microhabitats (e.g., soil pH) altered the soil microbiome and strongly contributed to C sequestration. Our findings reveal new evidence from soil microbiology for optimizing grazing exclusion duration to maintain multiple belowground ecosystem functions, providing promising suggestions for climate-smart and resource-efficient grasslands.This work was financially supported by the National Natural Science Foundation of China (32061123007, 41977031), the Strategic Priority Research Program of Chinese Academy of Sciences (XDB40020202), and the Natural Science Foundation of Hubei Province, China (2020CFA013). Manuel Delgado-Baquerizo acknowledges support from the Spanish Ministry of Science and Innovation for the I+D+i project PID2020-115813RA-I00 and TED2021-130908B-C41 funded by MCIN/AEI/10.13039/501100011033.Peer reviewe

Iron induces two distinct Ca²⁺ signalling cascades in astrocytes.

From Europe PMC via Jisc Publications RouterHistory: ppub 2021-05-01, epub 2021-05-05Publication status: PublishedFunder: National Natural Science Foundation of China (National Science Foundation of China); Grant(s): 81871852Iron is the fundamental element for numerous physiological functions. Plasmalemmal divalent metal ion transporter 1 (DMT1) is responsible for cellular uptake of ferrous (Fe2+), whereas transferrin receptors (TFR) carry transferrin (TF)-bound ferric (Fe3+). In this study we performed detailed analysis of the action of Fe ions on cytoplasmic free calcium ion concentration ([Ca2+]i) in astrocytes. Administration of Fe2+ or Fe3+ in μM concentrations evoked [Ca2+]i in astrocytes in vitro and in vivo. Iron ions trigger increase in [Ca2+]i through two distinct molecular cascades. Uptake of Fe2+ by DMT1 inhibits astroglial Na+-K+-ATPase, which leads to elevation in cytoplasmic Na+ concentration, thus reversing Na+/Ca2+ exchanger and thereby generating Ca2+ influx. Uptake of Fe3+ by TF-TFR stimulates phospholipase C to produce inositol 1,4,5-trisphosphate (InsP3), thus triggering InsP3 receptor-mediated Ca2+ release from endoplasmic reticulum. In summary, these findings reveal the mechanisms of iron-induced astrocytic signalling operational in conditions of iron overload

NusaCrowd: Open Source Initiative for Indonesian NLP Resources

We present NusaCrowd, a collaborative initiative to collect and unify existing resources for Indonesian languages, including opening access to previously non-public resources. Through this initiative, we have brought together 137 datasets and 118 standardized data loaders. The quality of the datasets has been assessed manually and automatically, and their value is demonstrated through multiple experiments. NusaCrowd's data collection enables the creation of the first zero-shot benchmarks for natural language understanding and generation in Indonesian and the local languages of Indonesia. Furthermore, NusaCrowd brings the creation of the first multilingual automatic speech recognition benchmark in Indonesian and the local languages of Indonesia. Our work strives to advance natural language processing (NLP) research for languages that are under-represented despite being widely spoken