Probabilistic Planning of Distribution Networks with Optimal DG Placement Under Uncertainties

This research paper presents an efficient methodology for distribution network planning under an uncertain environment. As an extension of our previous work presented at the ECCE Asia 2021 conference, here optimal placement and sizing of Renewable Energy Sources (RES)-based Distributed Generations (DGs) are determined considering the generation and load uncertainties. In addition, the optimal tap settings of off-load tap changing transformers present in a network are also determined. Probabilistic non-linear optimization is solved with a sensitivity-based technique to minimize the distribution network losses and improve its voltage stability. The proposed methodology is implemented on standard test systems like the IEEE 69 bus and the Indian 85 bus networks. Further, to determine its real-world functionality, the methodology is tested on a practical radial distribution network of 88 buses present in a remote Froan island of Norway. When compared with existing techniques, the proposed methodology provides much more efficient network planning solutions with lesser power losses. Developed on free and open-source software platforms, it also provides a reliable and cost-effective alternative to network operators to determine their network robustness.acceptedVersio

Unbiased taxonomic annotation of metagenomic samples

The classification of reads from a metagenomic sample using a reference taxonomy is usually based on first mapping the reads to the reference sequences and then classifying each read at a node under the lowest common ancestor of the candidate sequences in the reference taxonomy with the least classification error. However, this taxonomic annotation can be biased by an imbalanced taxonomy and also by the presence of multiple nodes in the taxonomy with the least classification error for a given read. In this article, we show that the Rand index is a better indicator of classification error than the often used area under thereceiver operating characteristic (ROC) curve andF-measure for both balanced and imbalanced reference taxonomies, and we also address the second source of bias by reducing the taxonomic annotation problem for a whole metagenomic sample to a set cover problem, for which a logarithmic approximation can be obtained in linear time and an exact solution can be obtained by integer linear programming. Experimental results with a proof-of-concept implementation of the set cover approach to taxonomic annotation in a next release of the TANGO software show that the set cover approach further reduces ambiguity in the taxonomic annotation obtained with TANGO without distorting the relative abundance profile of the metagenomic sample.Peer ReviewedPostprint (published version

Stochastic operation of energy constrained microgrids considering battery degradation

Power systems with high penetration of variable renewable generation are vulnerable to periods with low generation. An alternative to retain high dispatchable generation capacity is electric energy storage that enables utilization of surplus power, where the electric energy storage contributes to the security of supply. Such systems can be considered as energy-constrained, and the operation of the electric energy storage must balance the minimization of the current operating costs against the risk of not being able to meet the future demand. Safe and efficient operation requires stochastic methods with sufficient foresight. Operation dependent storage degradation is a complicating factor. This paper proposes a linear approximation of battery state-of-charge degradation and implements it in a stochastic dual dynamic programming based energy-management model in combination with cycling degradation. The long-term implications of degradation modeling in the daily operation are studied for a small Norwegian microgrid with variable renewable power generation and limited dispatchable generation capacity as well as battery and hydrogen storage to balance supply and demand. Our results show that the proposed strategy can prolong the expected battery lifetime by more than four years compared to the naive stochastic strategy but may cause increased degradation for other system resources. © 2022 The AuthorsStochastic operation of energy constrained microgrids considering battery degradationpublishedVersio

RELSAD: A Python package for reliability assessment of modern distribution systems

publishedVersio

Management at the service of research: ReOmicS, a quality management system for omics sciences

Management and research represent a binomial almost unknown, whose potentialities and requirements have not yet been fully exploited even if, recently, the scientific and social communities have felt the burden of producing results and data requiring at the same time reproducibility, reliability, safety and efficacy of the discoveries, as well as a profitable use of resources. A Quality Management System (QMS) could represent a valid tool for these purposes, improving the quality of the research. The research community could ask whether and how it is possible to apply this approach in a research laboratory without hindering their creativity, and what the possible benefits might be. On the other hand, an international standard for a quality management system appropriate for a research laboratory is yet to come. The choice, the design and the application of a QMS, inspired by the Good Laboratory Practices, in a research laboratory specialized on “omics” sciences, is fully described in this paper. Its application has already shown good outcomes as testified by specific metric of efficiency and effectiveness. The approach is innovative as there is no obvious requirement for research laboratories to develop and define quality objectives. The paper highlights how the QMS approach enhances the relationship with public and private sectors by increasing customer confidence and loyalty, as well as improving the overall performance of the laboratory in terms of throughput and value of research. These results encourage proposing it as a QMS model providing a new and scalable operational strategy to be applied in a research environment with the same target and even in a generic research laboratory

Subcutaneous administration of TC007 reduces disease severity in an animal model of SMA

Background Spinal Muscular Atrophy (SMA) is the leading genetic cause of infantile death. It is caused by the loss of functional Survival Motor Neuron 1 (SMN1). There is a nearly identical copy gene, SMN2, but it is unable to rescue from disease due to an alternative splicing event that excises a necessary exon (exon 7) from the majority of SMN2-derived transcripts. While SMNΔ7 protein has severely reduced functionality, the exon 7 sequences may not be specifically required for all activities. Therefore, aminoglycoside antibiotics previously shown to suppress stop codon recognition and promote translation read-through have been examined to increase the length of the SMNΔ7 C-terminus. Results Here we demonstrate that subcutaneous-administration of a read-through inducing compound (TC007) to an intermediate SMA model (Smn-/-; SMN2+/+; SMNΔ7) had beneficial effects on muscle fiber size and gross motor function. Conclusion Delivery of the read-through inducing compound TC007 reduces the disease-associated phenotype in SMA mice, however, does not significantly extend survival

Stem cell impairment at the host–microbiota interface in colorectal cancer

Colorectal cancer (CRC) initiation is believed to result from the conversion of normal intestinal stem cells (ISCs) into cancer stem cells (CSCs), also known as tumor-initiating cells (TICs). Hence, CRC evolves through the multiple acquisition of well-established genetic and epigenetic alterations with an adenoma–carcinoma sequence progression. Unlike other stem cells elsewhere in the body, ISCs cohabit with the intestinal microbiota, which consists of a diverse community of microorganisms, including bacteria, fungi, and viruses. The gut microbiota communicates closely with ISCs and mounting evidence suggests that there is significant crosstalk between host and microbiota at the ISC niche level. Metagenomic analyses have demonstrated that the host– microbiota mutually beneficial symbiosis existing under physiologic conditions is lost during a state of pathological microbial imbalance due to the alteration of microbiota composition (dysbiosis) and/or the genetic susceptibility of the host. The complex interaction between CRC and microbiota is at the forefront of the current CRC research, and there is growing attention on a possible role of the gut microbiome in the pathogenesis of CRC through ISC niche impairment. Here we primarily review the most recent findings on the molecular mechanism underlying the complex interplay between gut microbiota and ISCs, revealing a possible key role of microbiota in the aberrant reprogramming of CSCs in the initiation of CRC. We also discuss recent advances in OMICS approaches and single-cell analyses to explore the relationship between gut microbiota and ISC/CSC niche biology leading to a desirable implementation of the current precision medicine approaches

Enrichment of intestinal Lactobacillus by enhanced secretory IgA coating alters glucose homeostasis in P2rx7 −/− mice

The secretory immunoglobulin A (SIgA) in mammalian gut protects the organism from infections and contributes to host physiology by shaping microbiota composition. The mechanisms regulating the adaptive SIgA response towards gut microbes are poorly defined. Deletion of P2rx7, encoding for the ATP-gated ionotropic P2X7 receptor, leads to T follicular helper (Tfh) cells expansion in the Peyer\u2019s patches (PPs) of the small intestine, enhanced germinal centre (GC) reaction and IgA secretion; the resulting alterations of the gut microbiota in turn affects host metabolism. Here, we define gut microbiota modifications that correlate with deregulated SIgA secretion and metabolic alterations in P2rx7 12/ 12 mice. In particular, Lactobacillus shows enhanced SIgA coating in P2rx7 12/ 12 with respect to wild-type (WT) mice. The abundance of SIgA-coated lactobacilli positively correlates with Tfh cells number and body weight, suggesting Lactobacillus-specific SIgA response conditions host metabolism. Accordingly, oral administration of intestinal Lactobacillus isolates from P2rx7 12/ 12 mice to WT animals results in altered glucose homeostasis and fat deposition. Thus, enhanced SIgA production by P2X7 insufficiency promotes Lactobacillus colonization that interferes with systemic metabolic homeostasis. These data indicate that P2X7 receptor-mediated regulation of commensals coating by SIgA is important in tuning the selection of bacterial taxa, which condition host metabolism