A Study of Ineffective Investment Trust and Precious Metal Mining Issues

Inobject/target reconstruction and recognition based on laser radar data, the range value's accuracy is important. The range data accuracy depends on the accuracy in the laser radar's detector, especially the algorithm used for time-of-flight estimation. In this paper, a general direct-detection laser radar system applicable for hard-target measurements is modeled. The time- and range-dependent laser radar cross sections are derived for some simple geometric shapes (plane, cone, sphere, and paraboloid). The cross-section models are used, in simulations, to find the proper statistical distribution of uncertainties in time-of-flight range estimations. Three time-of-flight estimation algorithms are analyzed: peak detection, constant-fraction detection, and matched filter. The detection performance for various shape conditions and signal-to-noise ratios is analyzed. Two simple shape reconstruction examples are shown, and the detectors' performance is compared with the Cramér-Raolower bound. The performance of the peak detection and the constant-fraction detection is more dependent on the shape and noise level than that of the matched filter. For line fitting the matched filter performs close to the Cramér-Rao lower bound

Serum thymidine kinase 1 concentration as a predictive biomarker in prostate cancer

Background Thymidine kinase 1 (TK1) recycles DNA before cell division. We do not know if baseline blood concentrations of TK1 predict death in prostate cancer within 30 years. Our objective is to determine if there is an association between baseline levels of TK1 and future prostate cancer-specific mortality. Methods With a "proof of concept" approach, we performed a nested case-control study among 1782 individuals screened for prostate cancer between 1988 and 1989. The concentration of TK1 was measured in frozen serum from 330 men, 36 of whom have died of prostate cancer. The primary endpoint was prostate cancer-specific mortality and outcomes after 30 years were analyzed using logistic regression modeling odds ratios (Ors). Results The estimated OR (adjusted for age) for dying from prostate cancer among the men who had a TK1 value in the upper tertile was 2.39 (95% confidence interval 1.02-5.63). The corresponding OR, regardless of the cause of death, was 2.81 (1.24-6.34). Conclusions High levels of TK1 predicts death in prostate cancer within 30 years of follow-up

Profiling the serum protein corona of fibrillar human islet amyloid polypeptide

Amyloids may be regarded as native nanomaterials that form in the presence of complex protein mixtures. By drawing an analogy with the physicochemical properties of nanoparticles in biological fluids, we hypothesized that amyloids should form a protein corona in vivo that would imbue the underlying amyloid with a modified biological identity. To explore this hypothesis we characterized the protein corona of human islet amyloid polypeptide (IAPP) fibrils in FBS using two complementary methodologies developed herein; quartz crystal microbalance and ‘centrifugal capture’, coupled with nano-liquid chromatography tandem mass spectroscopy. Clear evidence for a significant protein corona was obtained. No trends were identified for amyloid corona proteins based on their physicochemical properties, while strong binding with IAPP fibrils occurred for linear proteins or multi-domain proteins with structural plasticity. Proteomic analysis identified amyloid-enriched proteins that are known to play significant roles in mediating cellular machinery and processing, potentially leading to pathological outcomes and therapeutic targets

A transcriptional timetable of autumn senescence

BACKGROUND: We have developed genomic tools to allow the genus Populus (aspens and cottonwoods) to be exploited as a full-featured model for investigating fundamental aspects of tree biology. We have undertaken large-scale expressed sequence tag (EST) sequencing programs and created Populus microarrays with significant gene coverage. One of the important aspects of plant biology that cannot be studied in annual plants is the gene activity involved in the induction of autumn leaf senescence. RESULTS: On the basis of 36,354 Populus ESTs, obtained from seven cDNA libraries, we have created a DNA microarray consisting of 13,490 clones, spotted in duplicate. Of these clones, 12,376 (92%) were confirmed by resequencing and all sequences were annotated and functionally classified. Here we have used the microarray to study transcript abundance in leaves of a free-growing aspen tree (Populus tremula) in northern Sweden during natural autumn senescence. Of the 13,490 spotted clones, 3,792 represented genes with significant expression in all leaf samples from the seven studied dates. CONCLUSIONS: We observed a major shift in gene expression, coinciding with massive chlorophyll degradation, that reflected a shift from photosynthetic competence to energy generation by mitochondrial respiration, oxidation of fatty acids and nutrient mobilization. Autumn senescence had much in common with senescence in annual plants; for example many proteases were induced. We also found evidence for increased transcriptional activity before the appearance of visible signs of senescence, presumably preparing the leaf for degradation of its components

Applying the FAIR Principles to Computational Workflows

Recent trends within computational and data sciences show an increasing recognition and adoption of computational workflows as tools for productivity, reproducibility, and democratized access to platforms and processing know-how. As digital objects to be shared, discovered, and reused, computational workflows benefit from the FAIR principles, which stand for Findable, Accessible, Interoperable, and Reusable. The Workflows Community Initiative's FAIR Workflows Working Group (WCI-FW), a global and open community of researchers and developers working with computational workflows across disciplines and domains, has systematically addressed the application of both FAIR data and software principles to computational workflows. We present our recommendations with commentary that reflects our discussions and justifies our choices and adaptations. Like the software and data principles on which they are based, these are offered to workflow users and authors, workflow management system developers, and providers of workflow services as guide rails for adoption and fodder for discussion. Workflows are becoming more prevalent as documented, automated instruments for data analysis, data collection, AI-based predictions, and simulations. The FAIR recommendations for workflows that we propose in this paper will maximize their value as research assets and facilitate their adoption by the wider community

Socialdemokratins fall och uppgång : Luleå 1917 - 1924

Validerat; 20101217 (root

Molecular characterization of metastatic ovarian cancer by MALDI imaging mass spectrometry.

Imaging mass spectrometry (IMS) is a novel technology which measures the spatial distribution of drugs, lipids, peptides and proteins across tissue sections by application of mass spectrometry (MS) directly to the section surface. Several hundred analytes can be measured across a tissue in a single IMS experiment, without the need for antibodies and without prior knowledge of tissue composition or structure. In the context of human cancers, the molecular information collected by IMS approaches has been used to grade cancers and predict patient survival. IMS is thus a potentially technology capable of providing valuable complementary information to classical histology and immuno-histochemistry. Ovarian cancers have the highest mortality of any gynaecological cancer. The high mortality results from late diagnosis due to the asymptomatic nature of ovarian malignancies. Advanced stage ovarian tumours will shed cancer cells into the abdominal cavity, where they subsequently implant into the peritoneum and form metastatic tumour nodules. Despite invasive surgery and adjuvant chemotherapy, there is a large increase in patient morbidity following peritoneal metastasis. Compounding this issue further is the absence of reliable grading systems for ovarian cancer and a subsequent lack of individualized treatments for specific cancer sub-types. As a result of the potential ability to grade tumours and provide patient prognoses based on IMS data, the molecular composition of ovarian metastatic tumours was investigated by IMS. The novelty of IMS required set up of a robust and reproducible workflow. Methods were thus optimized for IMS analysis of both frozen and formalin-fixed paraffin-embedded (FFPE) ovarian tumour tissue. Subsequently it was shown that optimization of available antigen retrieval and tryptic digest methods for accessing FFPE tissues could achieve higher tryptic peptide signal to noise at a better spatial resolution than methods available in the literature. As such, a complete tryptic peptide IMS workflow was developed alongside liquid chromatography (LC) and MS/MS based peptide identification. In conjunction with this workflow, methods for improving the matching of IMS peptides to LC-MS/MS identified peptides using internal calibrants and development of an in-house software tool were described. As a result of the work presented in this thesis, a complete tryptic peptide IMS workflow which could be applied to virtually any cancer tissue was developed. The application of this workflow, and exploratory k-means clustering, to ovarian peritoneal metastases showed that key tryptic peptides could be found which distinguish cancer tissue from the surrounding peritoneal stroma. This represented the first step in characterizing these metastatic tumours at the molecular level. The results in this thesis are a precursor to future work which will validate these peptide markers and develop a classification system for metastatic ovarian cancers based on patient survival and response to chemotherapy.Thesis (Ph.D.) -- University of Adelaide, School of Molecular and Biomedical Science, 201

Fallet Vattenfall: Hur hållbar är relationen mellan företag och intresseorganisationer?

Introduktion: Såväl samhälle som stat ställer krav på att företag ska ta ansvar för vilken påverkan verksamheten har på människor och miljö. Företag upprättar hållbarhetsredovisningar för att kommunicera graden av ansvarstagande till omvärlden. Även fast utformningen av hållbarhetsredovisningar är frivillig finns det olika riktlinjer för att se till att det som redovisas är relevant. En metod är att föra dialog med företagets intressenter. Åsikter om företag och verksamhetsaktiviteter kan skilja sig beroende på vem man frågar. Energiföretaget Vattenfall både hållbarhetsredovisar och för intressentdialoger samtidigt som stark kritik riktas mot företagets brist på ansvarstagande. Är hållbarhetsredovisningar ett kvitto på hållbarhet och vilket är egentligen syftet med intressentdialoger? Syfte: Öka förståelsen för konflikterna kring Vattenfalls verksamhet genom att närmre undersöka kommunikationen mellan företaget och relevanta intresseorganisationer. Metod: Kvalitativ abduktiv ansats och semistrukturerade intervjuer. Teoretisk referensram: Består av intressentteori och legitimitetsteori applicerade på Corporate Social Responsibility, Global Reporting Initiative, intressentdialoger, kommunikation, hållbarhetsredovisning och greenwashing. Vi har även inkluderat en modell för att förklara legitimitet. Empiri: Består av intervjuer med respondenter med anknytning till Jordens Vänner, Älvräddarna och Greenpeace. Däröver har vi använt års- och hållbarhetsredovisningar samt pressmeddelanden publicerade av Vattenfall. Slutsats: Utifrån tolkningar av hur respondenterna med anknytning till olika intresseorganisationer upplever företaget och kommunikationen dem emellan visade studien på ineffektiv användning av intressentdialogen. Analys av Vattenfalls bemötande av kritik stämmer däröver in på definitioner av olika greenwashingstrategier