Zeros and the functional equation of the quadrilateral zeta function

In this paper, we show that all real zeros of the bilateral Hurwitz zeta function $Z(s,a):=\zeta (s,a) + \zeta (s,1-a)$ with $1/4 \le a \le 1/2$ are on only the non-positive even integers exactly same as in the case of $(2^s-1) \zeta (s)$. We also prove that all real zeros of the bilateral periodic zeta function $P(s,a):={\rm{Li}}_s (e^{2\pi ia}) + {\rm{Li}}_s (e^{2\pi i(1-a)})$ with $1/4 \le a \le 1/2$ are on only the negative even integers just like $\zeta (s)$. Moreover, we show that all real zeros of the quadrilateral zeta function $Q(s,a):=Z(s,a) + P(s,a)$ with $1/4 \le a \le 1/2$ are on only the negative even integers. On the other hand, we prove that $Z(s,a)$, $P(s,a)$ and $Q(s,a)$ have at least one real zero in $(0,1)$ when $0<a<1/2$ is sufficiently small. The complex zeros of these zeta functions are also discussed when $1/4 \le a \le 1/2$ is rational or transcendental. As a corollary, we show that $Q(s,a)$ with rational $1/4 < a < 1/3$ or $1/3 < a < 1/2$ does not satisfy the analogue of the Riemann hypothesis even though $Q(s,a)$ satisfies the functional equation that appeared in Hamburger's or Hecke's theorem and all real zeros of $Q(s,a)$ are located at only the negative even integers again as in the case of $\zeta (s)$.Comment: 12 pages. We changed the title. Some typos are correcte

Inland wetlands mapping and vulnerability assessment using an integrated geographic information system and remote sensing techniques

The understanding of inland wetlands’ distribution and their level of vulnerability is important to enhance management and conservation efforts. The aim of the study was to map inland wetlands and assess their distribution pattern and vulnerability to natural and human disturbances such as climate change (temperature increase) and human activities by the year 2080. Inland wetland types i.e. forested/shrub, emergent and open water bodies were classified and mapped using maximum likelihood standard algorithm. The spatial distribution pattern of inland wetlands was examined using average nearest neighbor analysis. A weighted geospatial vulnerability analysis was developed using variables such as roads, land cover/ land use (developed and agricultural areas) and climate data (temperature) to predict potentially vulnerable inland wetland types. Inland wetlands were successfully classified and mapped with overall accuracy of about 73 percent. Clustered spatial distribution pattern was found among all inland wetland types with varied degree of clustering. The study found about 13 percent of open water bodies, 11 percent of forested/shrub and 7 percent of emergent wetlands potentially most vulnerable to human and natural stressors. This information could be used to improve wetland planning and management by wetland managers and other stakeholders

Prognostic value of prostate circulating cells detection in prostate cancer patients: a prospective study

In clinically organ-confined prostate cancer patients, bloodstream tumour cell dissemination generally occurs, and may be enhanced by surgical prostate manipulation. To evaluate cancer-cell seeding impact upon patient recurrence-free survival, 155 patients were prospectively enrolled then followed. Here, 57 patients presented blood prostate cell shedding preoperatively and intraoperatively (group I). Of the 98 preoperatively negative patients, 53 (54%) remained negative (group II) and 45 (46%) became intraoperatively positive (group III). Median biological and clinical recurrence-free time was far shorter in group I (36.2 months, P<0.0001) than in group II (69.6 months) but did not significantly differ in group II and III (69.6 months vs 65.0). Such 5-year follow-up data show that preoperative circulating prostate cells are an independent prognosis factor of recurrence. Moreover, tumour handling induces cancer-cell seeding but surgical blood dissemination does not accelerate cancer evolution

Continuity of transcriptomes among colorectal cancer subtypes based on meta-analysis

Background: Previous approaches to defining subtypes of colorectal carcinoma (CRC) and other cancers based on transcriptomes have assumed the existence of discrete subtypes. We analyze gene expression patterns of colorectal tumors from a large number of patients to test this assumption and propose an approach to identify potentially a continuum of subtypes that are present across independent studies and cohorts. Results: We examine the assumption of discrete CRC subtypes by integrating 18 published gene expression datasets and \u3e3700 patients, and contrary to previous reports, find no evidence to support the existence of discrete transcriptional subtypes. Using a meta-analysis approach to identify co-expression patterns present in multiple datasets, we identify and define robust, continuously varying subtype scores to represent CRC transcriptomes. The subtype scores are consistent with established subtypes (including microsatellite instability and previously proposed discrete transcriptome subtypes), but better represent overall transcriptional activity than do discrete subtypes. The scores are also better predictors of tumor location, stage, grade, and times of disease-free survival than discrete subtypes. Gene set enrichment analysis reveals that the subtype scores characterize T-cell function, inflammation response, and cyclin-dependent kinase regulation of DNA replication. Conclusions: We find no evidence to support discrete subtypes of the CRC transcriptome and instead propose two validated scores to better characterize a continuity of CRC transcriptomes

Impact of the spotted microarray preprocessing method on fold-change compression and variance stability

<p>Abstract</p> <p>Background</p> <p>The standard approach for preprocessing spotted microarray data is to subtract the local background intensity from the spot foreground intensity, to perform a log2 transformation and to normalize the data with a global median or a lowess normalization. Although well motivated, standard approaches for background correction and for transformation have been widely criticized because they produce high variance at low intensities. Whereas various alternatives to the standard background correction methods and to log2 transformation were proposed, impacts of both successive preprocessing steps were not compared in an objective way.</p> <p>Results</p> <p>In this study, we assessed the impact of eight preprocessing methods combining four background correction methods and two transformations (the log2 and the glog), by using data from the MAQC study. The current results indicate that most preprocessing methods produce fold-change compression at low intensities. Fold-change compression was minimized using the Standard and the Edwards background correction methods coupled with a log2 transformation. The drawback of both methods is a high variance at low intensities which consequently produced poor estimations of the p-values. On the other hand, effective stabilization of the variance as well as better estimations of the p-values were observed after the glog transformation.</p> <p>Conclusion</p> <p>As both fold-change magnitudes and p-values are important in the context of microarray class comparison studies, we therefore recommend to combine the Edwards correction with a hybrid transformation method that uses the log2 transformation to estimate fold-change magnitudes and the glog transformation to estimate p-values.</p

Highly Scalable, Wearable Surface‐Enhanced Raman Spectroscopy

The last two decades have witnessed a dramatic growth of wearable sensor technology, mainly represented by flexible, stretchable, on-skin electronic sensors that provide rich information of the wearer's health conditions and surroundings. A recent breakthrough in the field is the development of wearable chemical sensors based on surface-enhanced Raman spectroscopy (SERS) that can detect molecular fingerprints universally, sensitively, and noninvasively. However, while their sensing properties are excellent, these sensors are not scalable for widespread use beyond small-scale human health monitoring due to their cumbersome fabrication process and limited multifunctional sensing capabilities. Here, a highly scalable, wearable SERS sensor is demonstrated based on an easy-to-fabricate, low-cost, ultrathin, flexible, stretchable, adhesive, and biointegratable gold nanomesh. It can be fabricated in any shape and worn on virtually any surface for label-free, large-scale, in situ sensing of diverse analytes from low to high concentrations (10–106 × 10−9 m). To show the practical utility of the wearable SERS sensor, the sensor is tested for the detection of sweat biomarkers, drugs of abuse, and microplastics. This wearable SERS sensor represents a significant step toward the generalizability and practicality of wearable sensing technology

Dutch disease-cum-financialization booms and external balance cycles in developing countries

We formally investigate the medium-to-long-run dynamics emerging out of a Dutch disease-cum-financialization phenomenon. We take inspiration from the most recent Colombian development pattern. The “pure” Dutch disease first causes deindustrialization by permanently appreciating the economy’s exchange rate in the long run. Financialization, i.e. booming capital inflows taking place in a climate of natural resource-led financial over-optimism, causes medium-run exchange rate volatility and macroeconomic instability. This jeopardizes manufacturing development even further by raising macroeconomic uncertainty. We advise the adoption of capital controls and a developmentalist monetary policy to tackle these two distinct but often intertwined phenomena