Current AI in games : a review

As the graphics race subsides and gamers grow weary of predictable and deterministic game characters, game developers must put aside their “old faithful” finite state machines and look to more advanced techniques that give the users the gaming experience they crave. The next industry breakthrough will be with characters that behave realistically and that can learn and adapt, rather than more polygons, higher resolution textures and more frames-per-second. This paper explores the various artificial intelligence techniques that are currently being used by game developers, as well as techniques that are new to the industry. The techniques covered in this paper are finite state machines, scripting, agents, flocking, fuzzy logic and fuzzy state machines decision trees, neural networks, genetic algorithms and extensible AI. This paper introduces each of these technique, explains how they can be applied to games and how commercial games are currently making use of them. Finally, the effectiveness of these techniques and their future role in the industry are evaluated.

Acuity and severity of patients attending 28 Queensland hospitals emergency departments in 2008-09

Overcrowding of hospital Emergency Departments (EDs) in Australia is a complex issue of high public and professional prominence, resulted from a combination of increasing demands, increased complexity of care and Access Block. The aim of this study is to describe the distribution of the acuity and severity of current Queensland ED patients to better understand ED users...

Birth outcomes after spontaneous or assisted conception among infertile Australian women aged 28 to 36 years: A prospective, population-based study

Objective To examine the extent to which the odds of birth, pregnancy, or adverse birth outcomes are higher among women aged 28 to 36 years who use fertility treatment compared with untreated women. Design Prospective, population-based. Setting Not applicable. Patient(s) Participants in the ALSWH born in 1973 to 1978 who reported on their infertility and use of in vitro fertilization (IVF) or ovulation induction (OI). Intervention(s) Postal survey questionnaires administered as part of ALSWH. Main Outcome Measure(s) Among women treated with IVF or OI and untreated women, the odds of birth outcomes estimated by use of adjusted logistic regression modeling. Result(s) Among 7,280 women, 18.6% (n = 1,376) reported infertility. Half (53.0%) of the treated women gave birth compared with 43.8% of untreated women. Women with prior parity were less likely to use IVF compared with nulliparous women. Women using IVF or OI, respectively, were more likely to have given birth after treatment or be pregnant compared with untreated women. Women using IVF or OI were as likely to have ectopic pregnancies, stillbirths, or premature or low birthweight babies as untreated women. Conclusion(s) More than 40% of women aged 28–36 years reporting a history of infertility can achieve births without using treatment, indicating they are subfertile rather than infertile.

Deformation behaviour of nanocrystalline Mg-AI alloys during nanoindentation

The deformation behaviour of Mg-5%AI alloys and its dependence with gain size and strain rate were investigated using nanoindentation. The grain sizes were successfully reduced below 100 nm via mechanical alloying method. It was found that the strain rate sensitivity increased with decreasing grain size. The smaller activation volumes and the plastic deformation mechanisms involving grain boundary activities are considered to contribute to the increase of strain rate sensitivity in the nanocrystalline alloys.

Familial typical migraine: Significant linkage and localization of a gene to Xq24-28

In a previous study we found evidence for an X-linked genetic component for familial typical migraine in two large Australian white pedigrees, designated MF7 and MF14. Significant excess allele sharing was indicated by nonparametric linkage (NPL) analysis using GENEHUNTER (P=0.031 and P=0.012, respectively), with a combined analysis of the two pedigrees showing further increased evidence for linkage, producing a maximum NPL score of 2.87 (P=0.011 ) at DXS 1123 on Xq27. The present study was aimed at refining the localization of the migraine X-chromosomal component by typing additional markers, performing haplotype analysis and applying a more powerful technique in the analysis of linkage data from these two pedigrees. Results from the haplotype analyses, coupled with linkage analyses that produced a peak GENEHUNTER-PLUS LOD* score of 2.388 (P=0.0005), provide compelling evidence for the presence of a migraine susceptibility locus on chromosome Xq24-28.

The function and mechanisms of action of ghrelin and obestatin in ovarian cancer

In this study, we have demonstrated that the preproghrelin derived hormones, ghrelin and obestatin, may play a role in ovarian cancer. Ghrelin and obestatin stimulated an increase in cell migration in ovarian cancer cell lines and may play a role in cancer progression. Ovarian cancer is the leading cause of death among gynaecological cancers and is the sixth most common cause of cancer-related deaths in women in developed countries. As ovarian cancer is difficult to diagnose at a low tumour grade, two thirds of ovarian cancers are not diagnosed until the late stages of cancer development resulting in a poor prognosis for the patient. As a result, current treatment methods are limited and not ideal. There is an urgent need for improved diagnostic markers, as well better therapeutic approaches and adjunctive therapies for this disease. Ghrelin has a number of important physiological effects, including roles in appetite regulation and the stimulation of growth hormone release. It is also involved in regulating the immune, cardiovascular and reproductive systems and regulates sleep, memory and anxiety, and energy metabolism. Over the last decade, the ghrelin axis, (which includes the hormones ghrelin and obestatin and their receptors), has been implicated in the pathogenesis of many human diseases and it may t may also play an important role in the development of cancer. Ghrelin is a 28 amino acid peptide hormone that exists in two forms. Acyl ghrelin (usually referred to as ghrelin), has a unique n-octanoic acid post-translational modification (which is catalysed by ghrelin O-acyltransferase, GOAT), and desacyl ghrelin, which is a non-octanoylated form. Octanoylated ghrelin acts through the growth hormone secretagogue receptor type 1a (GHSR1a). GHSR1b, an alternatively spliced isoform of GHSR, is C-terminally truncated and does not bind ghrelin. Ghrelin has been implicated in the pathophysiology of a number of diseases Obestatin is a 23 amino acid, C-terminally amidated peptide which is derived from preproghrelin. Although GPR39 was originally thought to be the obestatin receptor this has been disproven, and its receptor remains unknown. Obestatin may have as diverse range of roles as ghrelin. Obestatin improves memory, inhibits thirst and anxiety, increases pancreatic juice secretion and has cardioprotective effects. Obestatin also has been shown to regulate cell proliferation, differentiation and apoptosis in some cell types. Prior to this study, little was known regarding the functions and mechanisms of action ghrelin and obestatin in ovarian cancer. In this study it was demonstrated that the full length ghrelin, GHSR1b and GOAT mRNA transcripts were expressed in all of the ovarian-derived cell lines examined (SKOV3, OV-MZ-6 and hOSE 17.1), however, these cell lines did not express GHSR1a. Ovarian cancer tissue of varying stages and normal ovarian tissue expressed the coding region for ghrelin, obestatin, and GOAT, but not GHSR1a, or GHSR1b. No correlations between cancer grade and the level of expression of these transcripts were observed. This study demonstrated for the first time that both ghrelin and obestatin increase cell migration in ovarian cancer cell lines. Treatment with ghrelin (for 72 hours) significantly increased cell migration in the SKOV3 and OV-MZ-6 ovarian cancer cell lines. Ghrelin (100 nM) stimulated cell migration in the SKOV3 (2.64 +/- 1.08 fold, p <0.05) and OV-MZ-6 (1.65 +/- 0.31 fold, p <0.05) ovarian cancer cell lines, but not in the representative normal cell line hOSE 17.1. This increase in migration was not accompanied by an increase in cell invasion through Matrigel. In contrast to other cancer types, ghrelin had no effect on proliferation. Ghrelin treatment (10nM) significantly decreased attachment of the SKOV3 ovarian cancer cell line to collagen IV (24.7 +/- 10.0 %, p <0.05), however, there were no changes in attachment to the other extracellular matrix molecules (ECM) tested (fibronectin, vitronectin and collagen I), and there were no changes in attachment to any of the ECM molecules in the OV-MZ-6 or hOSE 17.1 cell lines. It is, therefore, unclear if ghrelin plays a role in cell attachment in ovarian cancer. As ghrelin has previously been demonstrated to signal through the ERK1/2 pathway in cancer, we investigated ERK1/2 signalling in ovarian cancer cell lines. In the SKOV3 ovarian cancer cell line, a reduction in ERK1/2 phosphorylation (0.58 fold +/- 0.23, p <0.05) in response to 100 nM ghrelin treatment was observed, while no significant change in ERK1/2 signalling was seen in the OV-MZ-6 cell line with treatment. This suggests that this pathway is unlikely to be involved in mediating the increased migration seen in the ovarian cancer cell lines with ghrelin treatment. In this study ovarian cancer tissue of varying stages and normal ovarian tissue expressed the coding region for obestatin, however, no correlation between cancer grade and level of obestatin transcript expression was observed. In the ovarian-derived cell lines studied (SKOV3, OV-MZ-6 and hOSE 17.1) it was demonstrated that the full length preproghrelin mRNA transcripts were expressed in all cell lines, suggesting they have the ability to produce mature obestatin. This is the first study to demonstrate that obestatin stimulates cell migration and cell invasion. Obestatin induced a significant increase in migration in the SKOV3 ovarian cancer cell line with 10 nM (2.80 +/- 0.52 fold, p <0.05) and 100 nM treatments (3.12 +/- 0.68 fold, p <0.05) and in the OV-MZ-6 cancer cell line with 10 nM (2.04 +/- 0.10 fold, p <0.01) and 100 nM treatments (2.00 +/- 0.37 fold, p <0.05). Obestatin treatment did no affect cell migration in the hOSE 17.1normal ovarian epithelial cell line. Obestatin treatment (100 nM) also stimulated a significant increase in cell invasion in the OV-MZ-6 ovarian cancer cell line (1.45 fold +/- 0.13, p <0.05) and in the hOSE17.1 normal ovarian cell line cells (1.40 fold +/- 0.04 and 1.55 fold +/- 0.05 respectively, p <0.01) with 10 nM and 100 nM treatments. Obestatin treatment did not stimulate cell invasion in the SKOV3 ovarian cancer cell line. This lack of obestatin-stimulated invasion in the SKOV3 cell line may be a cell line specific result. In this study, obestatin did not stimulate cell proliferation in the ovarian cell lines and it has previously been shown to have no effect on cell proliferation in the BON-1 pancreatic neuroendocrine and GC rat somatotroph tumour cell lines. In contrast, obestatin has been shown to affect cell proliferation in gastric and thyroid cancer cell lines, and in some normal cell lines. Obestatin also had no effect on attachment of any of the cell lines to any of the ECM components tested (fibronectin, vitronectin, collagen I and collagen IV). The mechanism of action of obestatin was investigated further using a two dimensional-difference in gel electrophoresis (2D-DIGE) proteomic approach. After treatment with obestating (0, 10 and 100 nM), SKOV3 ovarian cancer and hOSE 17.1 normal ovarian cell lines were collected and 2D-DIGE analysis and mass spectrometry were performed to identify proteins that were differentially expressed in response to treatment. Twenty-six differentially expressed proteins were identified and analysed using Ingenuity Pathway Analysis (IPA). This linked 16 of these proteins in a network. The analysis suggested that the ERK1/2 MAPK pathway was a major mediator of obestatin action. ERK1/2 has previously been shown to be associated with obestatin-stimulated cell proliferation and with the anti-apoptotic effects of obestatin. Activation of the ERK1/2 signalling pathway by obestatin was, therefore, investigated in the SKOV3 and OV-MZ-6 ovarian cancer cell lines using anti-active antibodies and Western immunoblots. Obestatin treatment significantly decreased ERK1/2 phosphorylation at higher obestatin concentrations in both the SKOV3 (100 nM and 1000 nM) and OV-MZ-6 (1000 nM) cell lines compared to the untreated controls. Currently, very little is known about obestatin signalling in cancer. This thesis has demonstrated for the first time that the ghrelin axis may play a role in ovarian cancer migration. Ghrelin and obestatin increased cell migration in ovarian cancer cell lines, indicating that they may be a useful target for therapies that reduce ovarian cancer progression. Further studies investigating the role of the ghrelin axis using in vivo ovarian cancer metastasis models are warranted.

A vibrational spectroscopic study of the phosphate mineral whiteite CaMn++Mg2Al2(PO4)4(OH)2·8(H2O)

Vibrational spectroscopy enables subtle details of the molecular structure of whiteite to be determined. Single crystals of a pure phase from a Brazilian pegmatite were used. The infrared and Raman spectroscopy were applied to compare the molecular structure of whiteite with that of other phosphate minerals. The Raman spectrum of whiteite shows an intense band at 972 cm-1 assigned to the m1 PO3- 4 symmetric stretching vibrations. The low intensity Raman bands at 1076 and 1173 cm-1 are assigned to the m3 PO3- 4 antisymmetric stretching modes. The Raman bands at 1266, 1334 and 1368 cm-1 are assigned to AlOH deformation modes. The infrared band at 967 cm-1 is ascribed to the PO3- 4 m1 symmetric stretching vibrational mode. The infrared bands at 1024, 1072, 1089 and 1126 cm-1 are attributed to the PO3-4 m3 antisymmetric stretching vibrations. Raman bands at 553, 571 and 586 cm-1 are assigned to the m4 out of plane bending modes of the PO3- 4 unit. Raman bands at 432, 457, 479 and 500 cm-1 are attributed to the m2 PO4 and H2PO4 bending modes. In the 2600 to 3800 cm-1 spectral range, Raman bands for whiteite are found 3426, 3496 and 3552 cm-1 are assigned to AlOH stretching vibrations. Broad infrared bands are also found at 3186 cm-1. Raman bands at 2939 and 3220 cm-1 are assigned to water stretching vibrations. Raman spectroscopy complimented with infrared spectroscopy has enabled aspects of the structure of whiteite to be ascertained and compared with that of other phosphate minerals.

Facial emotion modulates the neural mechanisms responsible for short interval time perception

Emotionally arousing events can distort our sense of time. We used mixed block/event-related fMRI design to establish the neural basis for this effect. Nineteen participants were asked to judge whether angry, happy and neutral facial expressions that varied in duration (from 400 to 1,600 ms) were closer in duration to either a short or long duration they learnt previously. Time was overestimated for both angry and happy expressions compared to neutral expressions. For faces presented for 700 ms, facial emotion modulated activity in regions of the timing network Wiener et al. (NeuroImage 49(2):1728–1740, 2010) namely the right supplementary motor area (SMA) and the junction of the right inferior frontal gyrus and anterior insula (IFG/AI). Reaction times were slowest when faces were displayed for 700 ms indicating increased decision making difficulty. Taken together with existing electrophysiological evidence Ng et al. (Neuroscience, doi: 10.3389/fnint.2011.00077, 2011), the effects are consistent with the idea that facial emotion moderates temporal decision making and that the right SMA and right IFG/AI are key neural structures responsible for this effect.

Evaluation of Interconnect Fabrics for an Embedded MPSoC in 28 nm FD-SOI

Embedded many-core architectures contain dozens to hundreds of CPU cores that are connected via a highly scalable NoC interconnect. Our Multiprocessor-System-on-Chip CoreVAMPSoC combines the advantages of tightly coupled bus-based communication with the scalability of NoC approaches by adding a CPU cluster as an additional level of hierarchy. In this work, we analyze different cluster interconnect implementations with 8 to 32 CPUs and compare them in terms of resource requirements and performance to hierarchical NoCs approaches. Using 28nm FD-SOI technology the area requirement for 32 CPUs and AXI crossbar is 5.59mm2 including 23.61% for the interconnect at a clock frequency of 830 MHz. In comparison, a hierarchical MPSoC with 4 CPU cluster and 8 CPUs in each cluster requires only 4.83mm2 including 11.61% for the interconnect. To evaluate the performance, we use a compiler for streaming applications to map programs to the different MPSoC configurations. We use this approach for a design-space exploration to find the most efficient architecture and partitioning for an application.

What can game AI teach us?

Artificial intelligence (AI) applications typically involve encoding expert knowledge in machine form to find optimal solutions for a given problem. However, this paper deals with the opposite process of extracting new and human-comprehensible insights from emergent AI behaviour. Some examples of useful game-related insights drawn from observing AI players in action are presented.

Genome sequence of marine bacterium idiomarina sp. strain 28-8, isolated from Korean ark shells

Idiomarina sp. strain 28-8 is an aerobic, Gram-negative, flagellar bacterium isolated from the bodies of ark shells (Scapharca broughtonii) collected from underwater sediments in Gangjin Bay, South Korea. Here, we present the draft genome sequence of Idiomarina sp. 28-8 (2,971,606 bp, with a G+C content of 46.9%), containing 2,795 putative coding sequences.

Targeting Antiapoptotic Genes Upregulated by Androgen Withdrawal Using Antisense Oligodeoxynucleotides to Enhance Androgen-and Chemo-Sensitivity in Prostate Cancer

Androgen withdrawal is the only effective form of systemic therapy for men with advanced disease, producing symptomatic and/or objective response in 80% of patients. Unfortunately, androgen independent (AI) progression and death occurs within a few years in the majority of these cases (6). Prostate cancer is highly chemoresistant, with objective response rates of 10% and no demonstrated survival benefit (28). Hormone refractory prostate cancer (HRPC) is therefore the main obstacle to improving the survival and quality of life in patients with advanced disease, and novel therapeutic strategies that target the molecular basis of androgen and chemoresistance are required.

Meta-analysis of 28,141 individuals identifies common variants within five new loci that influence uric acid concentrations

Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, resulting in identification of 954 SNPs distributed across nine loci that exceeded the threshold of genome-wide significance, five of which are novel. Overall, the common variants associated with serum uric acid levels fall in the following nine regions: SLC2A9 (p = 5.2x10(-201)), ABCG2 (p = 3.1x10(-26)), SLC17A1 (p = 3.0x10(-14)), SLC22A11 (p = 6.7x10(-14)), SLC22A12 (p = 2.0x10(-9)), SLC16A9 (p = 1.1x10(-8)), GCKR (p = 1.4x10(-9)), LRRC16A (p = 8.5x10(-9)), and near PDZK1 (p = 2.7x10(-9)). Identified variants were analyzed for gender differences. We found that the minor allele for rs734553 in SLC2A9 has greater influence in lowering uric acid levels in women and the minor allele of rs2231142 in ABCG2 elevates uric acid levels more strongly in men compared to women. To further characterize the identified variants, we analyzed their association with a panel of metabolites. rs12356193 within SLC16A9 was associated with DL-carnitine (p = 4.0x10(-26)) and propionyl-L-carnitine (p = 5.0x10(-8)) concentrations, which in turn were associated with serum UA levels (p = 1.4x10(-57) and p = 8.1x10(-54), respectively), forming a triangle between SNP, metabolites, and UA levels. Taken together, these associations highlight additional pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia. In addition, these findings strongly support the hypothesis that transport proteins are key in regulating serum uric acid levels.