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Social media feeds are deeply personal spaces that reflect individual values and preferences. However, top-down, platform-wide content algorithms can reduce users' sense of agency and fail to account for nuanced experiences and values. Drawing on the paradigm of interactive machine teaching (IMT), an interaction framework for non-expert algorithmic adaptation, we map out a design space for teachable social media feed experiences to empower agential, personalized feed curation. To do so, we conducted a think-aloud study (N=24) featuring four social media platforms -- Instagram, Mastodon, TikTok, and Twitter -- to understand key signals users leveraged to determine the value of a post in their feed. We synthesized users' signals into taxonomies that, when combined with user interviews, inform five design principles that extend IMT into the social media setting. We finally embodied our principles into three feed designs that we present as sensitizing concepts for teachable feed experiences moving forward., Comment: CHI 2024

Advancements in large language models (LLMs) are poised to spark a proliferation of LLM-powered user experiences. In product teams, designers are often tasked with crafting user experiences that align with user needs. To involve designers and leverage their user-centered perspectives to create effective and responsible LLM-powered products, we introduce the practice of designerly adaptation for engaging with LLMs as an adaptable design material. We first identify key characteristics of designerly adaptation through a formative study with designers experienced in designing for LLM-powered products (N=12). These characteristics are 1) have a low technical barrier to entry, 2) leverage designers' unique perspectives bridging users and technology, and 3) encourage model tinkering. Based on this characterization, we build Canvil, a Figma widget that operationalizes designerly adaptation. Canvil supports structured authoring of system prompts to adapt LLM behavior, testing of adapted models on diverse user inputs, and integration of model outputs into interface designs. We use Canvil as a technology probe in a group-based design study (6 groups, N=17) to investigate the implications of integrating designerly adaptation into design workflows. We find that designers are able to iteratively tinker with different adaptation approaches and reason about interface affordances to enhance end-user interaction with LLMs. Furthermore, designers identified promising collaborative workflows for designerly adaptation. Our work opens new avenues for collaborative processes and tools that foreground designers' user-centered expertise in the crafting and deployment of LLM-powered user experiences.

UX practitioners face novel challenges when designing user interfaces for machine learning (ML)-enabled applications. Interactive ML paradigms, like AutoML and interactive machine teaching, lower the barrier for non-expert end users to create, understand, and use ML models, but their application to UX practice is largely unstudied. We conducted a task-based design study with 27 UX practitioners where we asked them to propose a proof-of-concept design for a new ML-enabled application. During the task, our participants were given opportunities to create, test, and modify ML models as part of their workflows. Through a qualitative analysis of our post-task interview, we found that direct, interactive experimentation with ML allowed UX practitioners to tie ML capabilities and underlying data to user goals, compose affordances to enhance end-user interactions with ML, and identify ML-related ethical risks and challenges. We discuss our findings in the context of previously established human-AI guidelines. We also identify some limitations of interactive ML in UX processes and propose research-informed machine teaching as a supplement to future design tools alongside interactive ML.

UX practitioners (UXPs) face novel challenges when working with and communicating artificial intelligence (AI) as a design material. We explore how UXPs communicate AI concepts when given hands-on experience training and experimenting with AI models. To do so, we conducted a task-based design study with 27 UXPs in which they prototyped and created a design presentation for a AI-enabled interface while having access to a simple AI model training tool. Through analyzing UXPs' design presentations and post-activity interviews, we found that although UXPs struggled to clearly communicate some AI concepts, tinkering with AI broadened common ground when communicating with technical stakeholders. UXPs also identified key risks and benefits of AI in their designs, and proposed concrete next steps for both UX and AI work. We conclude with a sensitizing concept and recommendations for design and AI tools to enhance multi-stakeholder communication and collaboration when crafting human-centered AI experiences.

Background: In a rapidly ageing population new and efficient ways of providing health and social support to older adults are required that not only preserve independence but also maintain quality of life and safety. Objective: The NEX project aims to develop an Internet of Things integrated system coupled with Artificial Intelligence to offer unobtrusive health and wellness monitoring to support older adults to live independently in their home environment. The primary objective of this study is to develop and evaluate the technical performance and user acceptability of “The NEX system”. The secondary objective is to apply machine learning algorithms to the data collected via the NEX system to identify and eventually predict changes in the routines of older adults in their own home environment. Methods: Mixed methods research (online survey and focus groups) was conducted with 426 participants including older adults (aged 60 and above), family caregivers, health care professionals and home care workers to inform the development of the NEX system (Phase 1). The primary outcome will be evaluated in two successive trials (the Friendly Trial (Phase 2) and the Action Research Cycle trial (Phase 3). The secondary objective will be explored in the Action Research trial (Phase 3). For the Friendly Trial, 7 older adult participants aged 60 years and above and living alone in their own homes for a 10-week period were enrolled in the trial. Thirty older adult participants aged 60 years and above and living alone in their own homes will be recruited for the Action Research trial for a 10-week period (Phase 3). Results: Phase 1 of the project (n=426) participants was completed in December 2020 and Phase 2 (n=7 participants for a 10-week pilot study) was completed in September 2021. The expected completion date for the third project phase (30 participants for 10-week usability study) is June 2022. Conclusions: The NEX project has considered the specific everyday needs of older adu

Robots that interact with humans in a physical space or application need to think about the person's posture, which typically comes from visual sensors like cameras and infra-red. Artificial intelligence and machine learning algorithms use information from these sensors either directly or after some level of symbolic abstraction, and the latter usually partitions the range of observed values to discretize the continuous signal data. Although these representations have been effective in a variety of algorithms with respect to accuracy and task completion, the underlying models are rarely interpretable, which also makes their outputs more difficult to explain to people who request them. Instead of focusing on the possible sensor values that are familiar to a machine, we introduce a qualitative spatial reasoning approach that describes the human posture in terms that are more familiar to people. This paper explores the derivation of our symbolic representation at two levels of detail and its preliminary use as features for interpretable activity recognition., Comment: Accepted for presentation at the AAAI 2022 Fall Symposium Series, in the symposium for Artificial Intelligence for Human-Robot Interaction

Motifs are distinctive recurring elements found in folklore that have significance as communicative devices in news, literature, press releases, and propaganda. Motifs concisely imply a large constellation of culturally-relevant information, and their broad usage suggests their cognitive importance as touchstones of cultural knowledge, making their detection a worthy step toward culturally-aware natural language processing tasks. Until now, folklorists and others interested in motifs have only extracted motifs from narratives manually. We present a preliminary report on the development of a system for automatically detecting motifs. We briefly describe an annotation effort to produce data for training motif detection, which is on-going. We describe our in-progress architecture in detail, which aims to capture, in part, how people determine whether or not a motif candidate is being used in a motific way. This description includes a test of an off-the-shelf metaphor detector as a feature for motif detection, which achieves a F1 of 0.35 on motifs and a macro-average F1 of 0.21 across four categories which we assign to motif candidates., Comment: 13 pages, 2 figures, Presented at The Ninth Advances in Cognitive Systems (ACS) Conference 2021 (arXiv:2201.06134)

ACS is an annual meeting for research on the initial goals of artificial intelligence and cognitive science, which aimed to explain the mind in computational terms and to reproduce the entire range of human cognitive abilities in computational artifacts. Many researchers remain committed to this original vision, and Advances in Cognitive Systems provides a place to present recent results and pose new challenges for the field. The meetings bring together researchers with interests in human-level intelligence, complex cognition, integrated intelligent systems, cognitive architectures, and related topics.

We have recently begun a project to develop a more effective and efficient way to marshal inferences from background knowledge to facilitate deep natural language understanding. The meaning of a word is taken to be the entities, predications, presuppositions, and potential inferences that it adds to an ongoing situation. As words compose, the minimal model in the situation evolves to limit and direct inference. At this point we have developed our computational architecture and implemented it on real text. Our focus has been on proving the feasibility of our design., Comment: 20 pages, 1 figure

The H+(CO)2 and D+(CO)2 molecular ions were investigated by infrared spectroscopy in the gas phase and in para-hydrogen matrices. In the gas phase, ions were generated in a supersonic molecular beam by a pulsed electrical discharge. After extraction into a time-of-flight mass spectrometer, the ions were mass selected and probed by infrared laser photodissociation spectroscopy in the 700 cm−1–3500 cm−1 region. Spectra were measured using either argon or neon tagging, as well as tagging with an excess CO molecule. In solid para-hydrogen, ions were generated by electron bombardment of a mixture of CO and hydrogen, and absorption spectra were recorded in the 400 cm−1–4000 cm−1 region with a Fourier-transform infrared spectrometer. A comparison of the measured spectra with the predictions of anharmonic theory at the CCSD(T)/ANO1 level suggests that the predominant isomers formed by either argon tagging or para-hydrogen isolation are higher lying (+7.8 kcal mol−1), less symmetric isomers, and not the global minimum proton-bound dimer. Changing the formation environment or tagging strategy produces other non-centrosymmetric structures, but there is no spectroscopic evidence for the centrosymmetric proton-bound dimer. The formation of higher energy isomers may be caused by a kinetic effect, such as the binding of X (=Ar, Ne, or H2) to H+(CO) prior to the formation of X H+(CO)2. Regardless, there is a strong tendency to produce non-centrosymmetric structures in which HCO+ remains an intact core ion.

The H+(CO)2 and D+(CO)2 molecular ions were investigated by infrared spectroscopy in the gas phase and in para-hydrogen matrices. In the gas phase, ions were generated in a supersonic molecular beam by a pulsed electrical discharge. After extraction into a time-of-flight mass spectrometer, the ions were mass selected and probed by infrared laser photodissociation spectroscopy in the 700 cm−1–3500 cm−1 region. Spectra were measured using either argon or neon tagging, as well as tagging with an excess CO molecule. In solid para-hydrogen, ions were generated by electron bombardment of a mixture of CO and hydrogen, and absorption spectra were recorded in the 400 cm−1–4000 cm−1 region with a Fourier-transform infrared spectrometer. A comparison of the measured spectra with the predictions of anharmonic theory at the CCSD(T)/ANO1 level suggests that the predominant isomers formed by either argon tagging or para-hydrogen isolation are higher lying (+7.8 kcal mol−1), less symmetric isomers, and not the global minimum proton-bound dimer. Changing the formation environment or tagging strategy produces other non-centrosymmetric structures, but there is no spectroscopic evidence for the centrosymmetric proton-bound dimer. The formation of higher energy isomers may be caused by a kinetic effect, such as the binding of X (=Ar, Ne, or H2) to H+(CO) prior to the formation of X H+(CO)2. Regardless, there is a strong tendency to produce non-centrosymmetric structures in which HCO+ remains an intact core ion.

The H+(CO)2 and D+(CO)2 molecular ions were investigated by infrared spectroscopy in the gas phase and in para-hydrogen matrices. In the gas phase, ions were generated in a supersonic molecular beam by a pulsed electrical discharge. After extraction into a time-of-flight mass spectrometer, the ions were mass selected and probed by infrared laser photodissociation spectroscopy in the 700 cm−1–3500 cm−1 region. Spectra were measured using either argon or neon tagging, as well as tagging with an excess CO molecule. In solid para-hydrogen, ions were generated by electron bombardment of a mixture of CO and hydrogen, and absorption spectra were recorded in the 400 cm−1–4000 cm−1 region with a Fourier-transform infrared spectrometer. A comparison of the measured spectra with the predictions of anharmonic theory at the CCSD(T)/ANO1 level suggests that the predominant isomers formed by either argon tagging or para-hydrogen isolation are higher lying (+7.8 kcal mol−1), less symmetric isomers, and not the global minimum proton-bound dimer. Changing the formation environment or tagging strategy produces other non-centrosymmetric structures, but there is no spectroscopic evidence for the centrosymmetric proton-bound dimer. The formation of higher energy isomers may be caused by a kinetic effect, such as the binding of X (=Ar, Ne, or H2) to H+(CO) prior to the formation of X H+(CO)2. Regardless, there is a strong tendency to produce non-centrosymmetric structures in which HCO+ remains an intact core ion.

Embedded software management requirements due to concerns about security vulnerabilities or for feature updates in the Internet of Things (IoT) deployments have raised the need for Firmware Update Over The Air (FUOTA). With FUOTA's support, security updates, new functionalities, and optimization patches can be deployed with little human intervention to embedded devices over their lifetime. However, supporting FUTOA over one of the most promising IoT networking technologies, LoRaWAN, is not a straightforward task due to LoRaWAN's limitations that do not provide for data bulk transfer such as a firmware image. Therefore, the LoRa Alliance has proposed new specifications to support multicast, fragmentation, and clock synchronization, which are essential features to enable efficient FUOTA in LoRaWAN. In this paper, we review these new specifications and evaluate the FUOTA process in order to quantify the impact of the different FUOTA parameters in terms of the firmware update time, the device's energy consumption, and the firmware update efficiency, showing different trade-offs among the parameters. For this, we developed FUOTASim, a simulation tool that allows us to determine the best FUOTA parameters.

Background and purpose: There is a large volume of heterogeneous studies across all Enhanced Recovery After Surgery (ERAS®) components within total hip and total knee replacement surgery. This multidisciplinary consensus review summarizes the literature, and proposes recommendations for the perioperative care of patients undergoing total hip replacement and total knee replacement with an ERAS program. Methods: Studies were selected with particular attention being paid to meta-analyses, randomized controlled trials, and large prospective cohort studies that evaluated the efficacy of individual items of the perioperative treatment pathway to expedite the achievement of discharge criteria. A consensus recommendation was reached by the group after critical appraisal of the literature. Results: This consensus statement includes 17 topic areas. Best practice includes optimizing preoperative patient education, anesthetic technique, and transfusion strategy, in combination with an opioid-sparing multimodal analgesic approach and early mobilization. There is insufficient evidence to recommend that one surgical technique (type of approach, use of a minimally invasive technique, prosthesis choice, or use of computer-assisted surgery) over another will independently effect achievement of discharge criteria. Interpretation: Based on the evidence available for each element of perioperative care pathways, the ERAS® Society presents a comprehensive consensus review, for the perioperative care of patients undergoing total hip replacement and total knee replacement surgery within an ERAS® program. This unified protocol should now be further evaluated in order to refine the protocol and verify the strength of these recommendations.

In summary, our evaluation found that the ACT Pill Testing Trial was implemented as planned, that the service was well received by patrons and stakeholders, and that the service impacted positively on patron knowledge, attitudes and behaviours. The 2019 Groovin the Moo festival Pill Testing Trial, implemented by Pill Testing Australia, was the second government-sanctioned trial of its type in Australia. It was designed and implemented collaboratively between the key stakeholders, primarily Pill Testing Australia, Cattleyard Promotions, and key ACT Government agencies ACT Health and ACT Policing. Enough lead time was available to develop the trial carefully, with the result that it was implemented as planned and produced the types of outputs that the key stakeholders expected to see. The service provided harm reduction information to 234 patrons and identified seven substances containing a potentially dangerous substance, N-ethyl pentylone. The experience of testing and the accompanying harm reduction brief interventions produced a number of positive results in terms of participants' self-reported drug harm reduction knowledge, their trust of health providers and other written sources of harm reduction information, and stated behavioural intentions regarding drug use. Overall, the evaluation produced no strong arguments against the development of further services that provide pill testing and harm reduction information for people who use illicit drugs. The findings are supportive of such initiatives.

The Australian alcohol and other drugs (AOD) sector has a diverse range of actors, including the nongovernment (NGO) service providers. Representing these services in each of Australian states and territories are AOD sector peak bodies. Their national network commissioned an evaluation of their capacity building (CB) activities and outcomes. The network and the evaluator developed a working definition of CB: Capacity building is a strategy that improves the ability of AOD workers, services and/or the broader AOD system to achieve better AOD health and social outcomes. The utilisation-focused evaluation (UFE) model was adopted for this project. The evaluation found that sound outcomes have been produced by the peaks’ CB work, and that includes valued changes in the service delivery work of the NGO sector. The CB strategies that are particularly important for attaining the desired outcomes were identified. The CB strategies and activities have been implemented well, and have delivered value for money, though sustainability remains a concern. The evaluation concluded that the peak bodies are ideally placed to deliver CB initiatives. The evaluation’s recommendations have been implemented, and process utilisation of the evaluation has been observed among its participants.

Finding a low dimensional representation of hierarchical, structured data described by a network remains a challenging problem in the machine learning community. An emerging approach is embedding these networks into hyperbolic space because it can naturally represent a network's hierarchical structure. However, existing hyperbolic embedding approaches cannot deal with attributed networks, in which nodes are annotated with additional attributes. These attributes might provide additional proximity information to constrain the representations of the nodes, which is important to learn high quality hyperbolic embeddings. To fill this gap, we introduce HEAT (Hyperbolic Embedding of ATributed networks), the first method for embedding attributed networks to a hyperbolic space. HEAT consists of 1) a modified random walk algorithm to obtain training samples that capture both topological and attribute similarity; and 2) a learning algorithm for learning hyperboloid embeddings from the obtained training samples. We show that by leveraging node attributes, HEAT can outperform a state-of-the-art Hyperbolic embedding algorithm on several downstream tasks. As a general embedding method, HEAT opens the door to hyperbolic manifold learning on a wide range of attributed and unattributed networks., Comment: 15 pages, 4 figures

Dendritic cells (DCs) and monocytes play a central role in pathogen sensing, phagocytosis, and antigen presentation and consist of multiple specialized subtypes. However, their identities and interrelationships are not fully understood. Using unbiased single-cell RNA sequencing (RNA-seq) of ~2400 cells, we identified six human DCs and four monocyte subtypes in human blood. Our study reveals a new DC subset that shares properties with plasmacytoid DCs (pDCs) but potently activates T cells, thus redefining pDCs; a new subdivision within the CD1C+ subset of DCs; the relationship between blastic plasmacytoid DC neoplasia cells and healthy DCs; and circulating progenitor of conventional DCs (cDCs). Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease.

The methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Recent studies in anaplastic glioma suggest a prognostic value for MGMT methylation. Investigation of pathogenetic and epigenetic features of this intriguingly distinct behavior requires accurate MGMT classification to assess high throughput molecular databases. Promoter methylation-mediated gene silencing is strongly dependent on the location of the methylated CpGs, complicating classification. Using the HumanMethylation450 (HM-450K) BeadChip interrogating 176 CpGs annotated for the MGMT gene, with 14 located in the promoter, two distinct regions in the CpG island of the promoter were identified with high importance for gene silencing and outcome prediction. A logistic regression model (MGMT-STP27) comprising probes cg1243587 and cg12981137 provided good classification properties and prognostic value (kappa=0.85; log-rank p<0.001) using a training-set of 63 glioblastomas from homogenously treated patients, for whom MGMT methylation was previously shown to be predictive for outcome based on classification by methylation-specific PCR. MGMT-STP27 was successfully validated in an independent cohort of chemo-radiotherapy-treated glioblastoma patients (n=50; kappa=0.88; outcome, log-rank p<0.001). Lower prevalence of MGMT methylation among CpG island methylator phenotype (CIMP) positive tumors was found in glioblastomas from The Cancer Genome Atlas than in low grade and anaplastic glioma cohorts, while in CIMP-negative gliomas MGMT was classified as methylated in approximately 50% regardless of tumor grade. The proposed MGMT-STP27 prediction model allows mining of datasets derived on the HM-450K or HM-27K BeadChip to explore effects of distinct epigenetic context of MGMT methylation suspected to modulate treatment resistance in different tumor types

This paper describes the design and development of a preliminary qualitative coding tool as well as a method to improve the process of achieving inter-coder reliability (ICR) in small teams. Software applications that support qualitative coding do not sufficiently assist collaboration among coders and overlook some fundamental issues related to ICR. We propose a new dimension of collaborative coding called "coders' certainty" and demonstrate its ability to illustrate valuable code disagreements that are missing from existing approaches. Through a case study, we describe the utility of our tool, Code Wizard, and how it helped a group of researchers effectively collaborate to code naturalistic observation data. We report the valuable lessons we learned from the development of our tool and method: (1) identifying coders' certainty constitutes an important part of determining the quality of data analysis and facilitates identifying overlapping and ambiguous codes, (2) making the details of coding process visible helps streamline the coding process and leads to a sense of ownership of the research results, and (3) there is valuable information hidden in coding disagreements that can be leveraged for improving the process of data analysis.

Dendritic cells (DCs) and monocytes play a central role in pathogen sensing, phagocytosis, and antigen presentation and consist of multiple specialized subtypes. However, their identities and interrelationships are not fully understood. Using unbiased single-cell RNA sequencing (RNA-seq) of ~2400 cells, we identified six human DCs and four monocyte subtypes in human blood. Our study reveals a new DC subset that shares properties with plasmacytoid DCs (pDCs) but potently activates T cells, thus redefining pDCs; a new subdivision within the CD1C+ subset of DCs; the relationship between blastic plasmacytoid DC neoplasia cells and healthy DCs; and circulating progenitor of conventional DCs (cDCs). Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease.

Dendritic cells (DCs) and monocytes play a central role in pathogen sensing, phagocytosis, and antigen presentation and consist of multiple specialized subtypes. However, their identities and interrelationships are not fully understood. Using unbiased single-cell RNA sequencing (RNA-seq) of ~2400 cells, we identified six human DCs and four monocyte subtypes in human blood. Our study reveals a new DC subset that shares properties with plasmacytoid DCs (pDCs) but potently activates T cells, thus redefining pDCs; a new subdivision within the CD1C+ subset of DCs; the relationship between blastic plasmacytoid DC neoplasia cells and healthy DCs; and circulating progenitor of conventional DCs (cDCs). Our revised taxonomy will enable more accurate functional and developmental analyses as well as immune monitoring in health and disease.

Social botnets have become an important phenomenon on social media. There are many ways in which social bots can disrupt or influence online discourse, such as, spam hashtags, scam twitter users, and astroturfing. In this paper we considered one specific social botnet in Twitter to understand how it grows over time, how the content of tweets by the social botnet differ from regular users in the same dataset, and lastly, how the social botnet may have influenced the relevant discussions. Our analysis is based on a qualitative coding for approximately 3000 tweets in Arabic and English from the Syrian social bot that was active for 35 weeks on Twitter before it was shutdown. We find that the growth, behavior and content of this particular botnet did not specifically align with common conceptions of botnets. Further we identify interesting aspects of the botnet that distinguish it from regular users., Comment: 13 pages, 4 figures, Presented at the ACM conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2016)

PurposeThe phenotypic manifestations of cerebral cavernous malformation disease caused by rare PDCD10 mutations have not been systematically examined, and a mechanistic link to Rho kinase-mediated hyperpermeability, a potential therapeutic target, has not been established.MethodsWe analyzed PDCD10 small interfering RNA-treated endothelial cells for stress fibers, Rho kinase activity, and permeability. Rho kinase activity was assessed in cerebral cavernous malformation lesions. Brain permeability and cerebral cavernous malformation lesion burden were quantified, and clinical manifestations were assessed in prospectively enrolled subjects with PDCD10 mutations.ResultsWe determined that PDCD10 protein suppresses endothelial stress fibers, Rho kinase activity, and permeability in vitro. Pdcd10 heterozygous mice have greater lesion burden than other Ccm genotypes. We demonstrated robust Rho kinase activity in murine and human cerebral cavernous malformation vasculature and increased brain vascular permeability in humans with PDCD10 mutation. Clinical phenotype is exceptionally aggressive compared with the more common KRIT1 and CCM2 familial and sporadic cerebral cavernous malformation, with greater lesion burden and more frequent hemorrhages earlier in life. We first report other phenotypic features, including scoliosis, cognitive disability, and skin lesions, unrelated to lesion burden or bleeding.ConclusionThese findings define a unique cerebral cavernous malformation disease with exceptional aggressiveness, and they inform preclinical therapeutic testing, clinical counseling, and the design of trials.Genet Med 17 3, 188-196.

Organic farming, a low intensity system, may offer benefits for a range of taxa, but what affects the extent of those benefits is imperfectly understood. We explored the effects of organic farming and landscape on the activity density and species density of spiders and carabid beetles, using a large sample of paired organic and conventional farms in the UK. Spider activity density and species density were influenced by both farming system and surrounding landscape. Hunting spiders, which tend to have lower dispersal capabilities, had higher activity density, and more species were captured, on organic compared to conventional farms. There was also evidence for an interaction, as the farming system effect was particularly marked in the cropped area before harvest and was more pronounced in complex landscapes (those with little arable land). There was no evidence for any effect of farming system or landscape on web-building spiders (which include the linyphiids, many of which have high dispersal capabilities). For carabid beetles, the farming system effects were inconsistent. Before harvest, higher activity densities were observed in the crops on organic farms compared with conventional farms. After harvest, no difference was detected in the cropped area, but more carabids were captured on conventional compared to organic boundaries. Carabids were more species-dense in complex landscapes, and farming system did not affect this. There was little evidence that non-cropped habitat differences explained the farming system effects for either spiders or carabid beetles. For spiders, the farming system effects in the cropped area were probably largely attributable to differences in crop management; reduced inputs of pesticides (herbicides and insecticides) and fertilisers are possible influences, and there was some evidence for an effect of non-crop plant species richness on hunting spider activity density. The benefits of organic farming may be greatest for taxa with lower d

PurposeThe phenotypic manifestations of cerebral cavernous malformation disease caused by rare PDCD10 mutations have not been systematically examined, and a mechanistic link to Rho kinase-mediated hyperpermeability, a potential therapeutic target, has not been established.MethodsWe analyzed PDCD10 small interfering RNA-treated endothelial cells for stress fibers, Rho kinase activity, and permeability. Rho kinase activity was assessed in cerebral cavernous malformation lesions. Brain permeability and cerebral cavernous malformation lesion burden were quantified, and clinical manifestations were assessed in prospectively enrolled subjects with PDCD10 mutations.ResultsWe determined that PDCD10 protein suppresses endothelial stress fibers, Rho kinase activity, and permeability in vitro. Pdcd10 heterozygous mice have greater lesion burden than other Ccm genotypes. We demonstrated robust Rho kinase activity in murine and human cerebral cavernous malformation vasculature and increased brain vascular permeability in humans with PDCD10 mutation. Clinical phenotype is exceptionally aggressive compared with the more common KRIT1 and CCM2 familial and sporadic cerebral cavernous malformation, with greater lesion burden and more frequent hemorrhages earlier in life. We first report other phenotypic features, including scoliosis, cognitive disability, and skin lesions, unrelated to lesion burden or bleeding.ConclusionThese findings define a unique cerebral cavernous malformation disease with exceptional aggressiveness, and they inform preclinical therapeutic testing, clinical counseling, and the design of trials.Genet Med 17 3, 188-196.

Organic farming, a low intensity system, may offer benefits for a range of taxa, but what affects the extent of those benefits is imperfectly understood. We explored the effects of organic farming and landscape on the activity density and species density of spiders and carabid beetles, using a large sample of paired organic and conventional farms in the UK. Spider activity density and species density were influenced by both farming system and surrounding landscape. Hunting spiders, which tend to have lower dispersal capabilities, had higher activity density, and more species were captured, on organic compared to conventional farms. There was also evidence for an interaction, as the farming system effect was particularly marked in the cropped area before harvest and was more pronounced in complex landscapes (those with little arable land). There was no evidence for any effect of farming system or landscape on web-building spiders (which include the linyphiids, many of which have high dispersal capabilities). For carabid beetles, the farming system effects were inconsistent. Before harvest, higher activity densities were observed in the crops on organic farms compared with conventional farms. After harvest, no difference was detected in the cropped area, but more carabids were captured on conventional compared to organic boundaries. Carabids were more species-dense in complex landscapes, and farming system did not affect this. There was little evidence that non-cropped habitat differences explained the farming system effects for either spiders or carabid beetles. For spiders, the farming system effects in the cropped area were probably largely attributable to differences in crop management; reduced inputs of pesticides (herbicides and insecticides) and fertilisers are possible influences, and there was some evidence for an effect of non-crop plant species richness on hunting spider activity density. The benefits of organic farming may be greatest for taxa with lower d

The conceptual framework of a new system, Collaborative Refinery, is motivated by a scenario involving the creation of an FAQ. The scenario introduces the concepts of collecting, culling, organizing and distilling. Distilling is a specialized form of collaborative authoring with support for content selection and genre. The Web-based user interface supporting access to the four conceptual functions is presened in detail. As well, the system architecture and a current implementation are described in detail. Several research directions are discussed with respect to Collaborative Refinery. Collaborative Refinery is related to prior research in personal information management, collaborative authoring, and shared workspaces.

The conceptual framework of a new system, Collaborative Refinery, is motivated by a scenario involving the creation of an FAQ. The scenario introduces the concepts of collecting, culling, organizing and distilling. Distilling is a specialized form of collaborative authoring with support for content selection and genre. The Web-based user interface supporting access to the four conceptual functions is presened in detail. As well, the system architecture and a current implementation are described in detail. Several research directions are discussed with respect to Collaborative Refinery. Collaborative Refinery is related to prior research in personal information management, collaborative authoring, and shared workspaces.

Reports on publications and presentations done during the quarter. Summarizes research plan going forward. Describes new research questions identified during the quarter.

Reports on publications and presentations done during the quarter. Summarizes research plan going forward. Describes new research questions identified during the quarter.

Issue: Since the mid-1990s, there have been calls to make naloxone, a prescription-only medicine in many countries, available to heroin and other opioid users and their peers and family members to prevent overdose deaths. Context: In Australia there were

Naive T cell activation is normally restricted to the lymphoid organs, in part because of their limited ability to migrate into the parenchyma of peripheral tissues. The liver vasculature is unique, however, and circulating leukocytes within the hepatic sinusoids have direct access to liver-resident cells, which include an abundant population of Kupffer cells. It is well accepted that recognition of cognate Ag within the liver leads to naive CD8+T cell activation in situ, but it is unclear whether the liver also supports naive CD4+T cell activation. In this study, we show that naive CD4+T cells can be activated to proliferate in the liver when cognate Ag expression is induced in hepatocytes by recombinant adeno-associated viral vectors. Ag-specific retention and activation of naive CD4+T cells within the liver are independent of lymphoid tissues but dependent on a clodronate liposome-sensitive population of liver-resident phagocytic cells. To our knowledge, this study provides the first unequivocal evidence that naive CD4+T cells can be activated in a nonlymphoid organ. It also gives critical insight into how CD4+T cells specific for Ag expressed in the liver are recruited to participate in protective or pathological responses during hepatotropic infections and autoimmune liver disease.

One way sunlight causes skin cancer is by suppressing anti-tumor immunity. A major mechanism involves altering mast cell migration via the C-X-C motif chemokine receptor 4–C-X-C motif chemokine ligand 12 (CXCR4-CXCL12) chemokine pathway. We have discovered that pharmacologically blocking this pathway with the CXCR4 antagonist AMD3100 prevents both UV radiation-induced immune suppression and skin cancer. The majority of control mice receiving UV-only developed histopathologically confirmed squamous cell carcinomas. In contrast, skin tumor incidence and burden was significantly lower in AMD3100-treated mice. Perhaps most striking was that AMD3100 completely prevented the outgrowth of latent tumors that occurred once UV irradiation ceased. AMD3100 protection from UV immunosuppression and skin cancer was associated with reduced mast cell infiltration into the skin, draining lymph nodes, and the tumor itself. Thus a major target of CXCR4 antagonism was the mast cell. Our results indicate that interfering with UV-induced CXCL12 by antagonizing CXCR4 significantly inhibits skin tumor development by blocking UV-induced effects on mast cells. Hence, the CXCR4-CXCL12 chemokine pathway is a novel therapeutic target in the prevention of UV-induced skin cancer.

One way sunlight causes skin cancer is by suppressing anti-tumor immunity. A major mechanism involves altering mast cell migration via the C-X-C motif chemokine receptor 4–C-X-C motif chemokine ligand 12 (CXCR4-CXCL12) chemokine pathway. We have discovered that pharmacologically blocking this pathway with the CXCR4 antagonist AMD3100 prevents both UV radiation-induced immune suppression and skin cancer. The majority of control mice receiving UV-only developed histopathologically confirmed squamous cell carcinomas. In contrast, skin tumor incidence and burden was significantly lower in AMD3100-treated mice. Perhaps most striking was that AMD3100 completely prevented the outgrowth of latent tumors that occurred once UV irradiation ceased. AMD3100 protection from UV immunosuppression and skin cancer was associated with reduced mast cell infiltration into the skin, draining lymph nodes, and the tumor itself. Thus a major target of CXCR4 antagonism was the mast cell. Our results indicate that interfering with UV-induced CXCL12 by antagonizing CXCR4 significantly inhibits skin tumor development by blocking UV-induced effects on mast cells. Hence, the CXCR4-CXCL12 chemokine pathway is a novel therapeutic target in the prevention of UV-induced skin cancer.

In July, James gave a full day tutorial entitled Actions, Objects, and their Habitats at the Summer School in Cognitive Linguistics in Bangor, Wales, with this abstract. In this talk, I outline the challenges facing linguistic theories and computational language modeling in the attempt to contextualize linguistic knowledge in a non-linguistic world. I will focus on two aspects of contextualization of meaning: sentential semantic enrichment, involving extra-compositional mechanisms, such as coercion, co-composition, and other semantic devices used in Generative Lexicon Theory. The second aspect involves the embedding of linguistic utterances within the contexts of their use by speakers, mediated through deeper representational structures. I introduce the notion of 'conceptual habitat', for the frame, script, and affordance based information associated with linguistic expressions. These habitats compose to create 'minimal simulations', which are temporally traced minimal models, constructed from the use of linguistic expressions in specific contextualized frames, interpreted from a particular point of view. Minimal simulation is shown to be a computationally tractable approach to the dynamic interpretation of contexts, by virtue of the perspective-based constraints imposed., Prepared in cooperation with Brandeis University, Waltham, MA.

We analyze the stability of standard, buffered, slotted-Aloha systems. Specifically, we consider a set of users, each equipped with an infinite buffer. Packets arrive into user i's buffer according to some stationary ergodic Markovian process of intensity lambda(i). At the beginning of each slot, if user i has packets in its buffer, it attempts to transmit a packet with fixed probability p(i) over a shared resource/channel. The transmission is successful only when no other user attempts to use the channel. The stability of such systems has been open since their very first analysis in 1979 by Tsybakov and Mikhailov. In this paper, we propose an approximate stability condition that is provably exact when the number of users grows large. We provide theoretical evidence and numerical experiments to explain why the proposed approximate stability condition is extremely accurate even for systems with a restricted number of users (even two or three)., QC 20121009

This thesis, which is divided into five papers, explores biased decision making in naturalistic environments and its implications for the efficiency of financial markets and forecasts of competitive event outcomes. Betting markets offer a valuable real world decision making context, allowing analysis that is not possible using regular financial market data. The first paper surveys studies that have employed betting markets to investigate biased decision making and discusses why the extent of these biases is significantly less than in the laboratory. The second paper addresses unresolved issues relating to noise trading and herding in financial markets, by showing that noise trading is associated with increased market efficiency, that the extent of herding differs depending on the direction and timing of changes in market prices, and that this results in an economically significant inefficiency. The findings of this paper have important policy implications for wider financial markets: regulatory measures to protect investors from the destabilizing effects of noise appear to be self-defeating and herding is particularly prevalent when uninformed traders perceive that informed traders are participating in the market. The third and fourth papers address the favourite-longshot bias (FLB), where market prices under-/over-estimate high/low probability outcomes. These papers demonstrate that previous explanations of the bias are inconsistent with evidence of trading in UK betting markets by developing and testing the predictions of models that explain the bias in terms of competition between market makers and the demand preferences of bettors. Moreover, it is definitively shown that, when no market maker is involved, the bias is due to cognitive errors of traders rather than their preference for risk, because only prospect theory, and not risk-love, can explain a reduced FLB in events with strong favourites. The final chapter explores methodological concerns rel

Fog has always been a difficult phenomenon to forecast. Its unpredictable nature and propensity to quickly decrease visibilities have had adverse effects on military operations for many years across the Korean peninsula. It is particularly difficult to prepare forecasts or plan operations for remote locations with limited fog detection ability. For detection at night, over large areas, and in remote locations, satellite observations are the best solution. This thesis used NASA MODIS satellite imagery to create an abbreviated climatology data set for remote areas across the Korean peninsula. Imagery from the Terra and Aqua near-polar orbiting satellites was used, providing four images per day: one daytime and one nighttime pass for each satellite. Two decision trees were developed to use as guidelines for fog detection by daytime and nighttime satellite images. It was not always possible to unambiguously determine if fog was in each scene, so various categories were created to supplement a fog or no fog decision. The four midseason months (October 2005, January 2006, April 2006, and July 2006), were analyzed to create a climatology database. The results are tabulated using different variables to make useful comparisons, like day-versus-night or Terra-versus-Aqua. The new totals are compared visually with bar charts and statistically to identify trends that might give insight to planners and forecasters. Seasonal and nocturnal patterns are very evident while differences between the results from two satellites are less obvious. Future work is needed to expand the climatology and increase the statistical results from this study., http://archive.org/details/asatellitebasedf109453452, US Air Force (USAF) author., Approved for public release; distribution is unlimited.

This thesis, which is divided into five papers, explores biased decision making in naturalistic environments and its implications for the efficiency of financial markets and forecasts of competitive event outcomes. Betting markets offer a valuable real world decision making context, allowing analysis that is not possible using regular financial market data. The first paper surveys studies that have employed betting markets to investigate biased decision making and discusses why the extent of these biases is significantly less than in the laboratory. The second paper addresses unresolved issues relating to noise trading and herding in financial markets, by showing that noise trading is associated with increased market efficiency, that the extent of herding differs depending on the direction and timing of changes in market prices, and that this results in an economically significant inefficiency. The findings of this paper have important policy implications for wider financial markets: regulatory measures to protect investors from the destabilizing effects of noise appear to be self-defeating and herding is particularly prevalent when uninformed traders perceive that informed traders are participating in the market. The third and fourth papers address the favourite-longshot bias (FLB), where market prices under-/over-estimate high/low probability outcomes. These papers demonstrate that previous explanations of the bias are inconsistent with evidence of trading in UK betting markets by developing and testing the predictions of models that explain the bias in terms of competition between market makers and the demand preferences of bettors. Moreover, it is definitively shown that, when no market maker is involved, the bias is due to cognitive errors of traders rather than their preference for risk, because only prospect theory, and not risk-love, can explain a reduced FLB in events with strong favourites. The final chapter explores methodological concerns rel

A notable feature of Australian drug policy is the limited public and professional attention given to the financial costs of drug abuse and to the levels and patterns of government expenditures incurred in preventing and responding to this. Since 1991, Collins and Lapsley have published scholarly reports documenting the social costs of drug abuse in Australia and their reports also contain estimates of governments' drug budgets: revenue and expenditures. They show that, in 2004-2005, Australian governments expended at least $5288 million on drug abuse, with 50% of the expenditure directed to preventing and dealing with alcohol-related problems, 45% to illicit drugs and just 5% to tobacco. Some 60% of the expenditure was directed at drug crime and 37% at health interventions. This pattern of resource allocation does not adequately reflect an evidence-informed policy orientation in that it largely fails to focus on the drug types that are the sources of the most harm (tobacco and alcohol rather than illicit drugs), and the sectors for which we have the strongest evidence of the cost-effectiveness of the available interventions (treatment and harm reduction rather than legislation and law enforcement). The 2010-2014 phase of Australia's National Drug Strategy should include incremental changes to the resource allocation mix, and not simply maintain the historical resource allocation formulae.

We study an interacting particle system whose dynamics depends on an interacting random environment. As the number of particles grows large, the transition rate of the particles slows down (perhaps because they share a common resource of fixed capacity). The transition rate of a particle is determined by its state, by the empirical distribution of all the particles and by a rapidly varying environment. The transitions of the environment are determined by the empirical distribution of the particles. We prove the propagation of chaos on the path space of the particles and establish that the limiting trajectory of the empirical measure of the states of the particles satisfies a deterministic differential equation. This deterministic differential equation involves the time averages of the environment process. We apply the results on particle systems to understand the behavior of computer networks where users access a shared resource using a distributed random Medium Access Control (MAC) algorithm. MAC algorithms are used in all Local Area Network (LAN), and have been notoriously difficult to analyze. Our analysis allows us to provide simple and explicit expressions of the network performance under such algorithms., QC 20110303

Research has shown that creating animations of science concepts enhances preservice teachers understanding of science content (Hoban, 2007) but a possible problem with student-generated animations is that some preservice elementary teachers may not fully understand or represent a science concept correctly. The objective of this study was to investigate whether involving preservice elementary teachers in a three phase framework whereby they create, review and publish their slowmations to a web site (Teacher Tube) improved their science content knowledge and whether uploading to Teacher Tube was a feasible process for preservice teachers. The study was underpinned by the theoretical framework of constructionism whereby personal and social influences on learning interact in the process of constructing and displaying an artifact as a representation of learning (Papert, 1980; 1991). This study involved two cohorts of preservice teachers who were allocated science topics as the focus for creating their animation in a science method course. As a result of creating, reviewing and publishing animations on a web site (Teacher Tube), 19/31 had a majomajor increase in science understanding, 9/31 experienced a minor increase and 3/31 experienced little or no increase. Creating their own animations of science concepts was an innovative way for the preservice teachers to engage with science content but it was challenging for most of them to upload their animation to the web site.