On a generalized Auslander-Reiten conjecture

We study the symmetric Auslander condition (SAC) which is equivalent to the generalized Auslander-Reiten condition (GARC). First, we affirmatively answer a question posed by Celikbas and Takahashi, that is, the equivalence of (SAC) and the symmetric Auslander condition for modules with constant rank (SACC). As a corollary of the result, we also give the equivalence of (SAC) for $R$ and $R/xR$, where $x$ is an $R$-regular element. Secondly, we explore (SAC) among ring homomorphisms $R \to S$ of local rings. We prove that if $S$ satisfies (SAC) (resp. Auslander-Reiten conjecture), then $R$ also satisfies (SAC) (resp. Auslander-Reiten conjecture) if the flat dimension of $S$ over $R$ is finite. We also prove that $R$ satisfies (SAC) implies that $S$ satisfies (SAC) if $R$ is Gorenstein, $S=R/Q^\ell$, where $Q$ is generated by a regular sequence of $R$ and the length of the sequence is at least $\ell$. This is a consequence of more general results about Ulrich ideals proved in this paper. Applying these results to deteminantal rings and numerical semigroup rings, we provide new classes of rings satisfying (SAC).Comment: Substantial reorganization. Comments are welcome

Colitis Following Initiation of Sofosbuvir and Simeprevir for Genotype 1 Hepatitis C.

Sofosbuvir and simeprevir are used for the treatment of chronic hepatitis C (HCV) genotype 1. Both drugs have been well-tolerated, with diarrhea noted in 6% cases with sofosbuvir, 16% with sofosbuvir plus simeprevir, and 0% with simeprevir. No prior reports exist of colitis secondary to either drug or their combination. We report a patient with no prior history of inflammatory bowel disease who developed significant bloody diarrhea within 2 weeks of sofosbuvir/simeprevir initiation. Colonoscopy and biopsy confirmed pancolitis, which responded to mesalamine and completion of sofosbuvir/simeprevir

Resveratrol Regulates Antioxidant Status, Inhibits Cytokine Expression and Restricts Apoptosis in Carbon Tetrachloride Induced Rat Hepatic Injury

Recent studies indicate the chemopreventive role of resveratrol in many animal models like ischemia, rheumatoid arthritis, human cancer, and diabetes. The present study was designed to investigate the chemopreventive potential of resveratrol in rat hepatic injury model by carbon tetrachloride. Male Wistar rats were treated with carbon tetrachloride (0.4 g/kg body weight) intraperitoneally daily for 8 weeks. Resveratrol (100 mg/kg, 200 mg/kg body weight) was given orally from first day until the last day of experiment. The investigation assesses the effect of resveratrol on morphological, oxidative status, histopathological, immunohistochemical, and apoptotic analysis in carbon tetrachloride-challenged liver tissue. The study indicated that the inflammatory cytokines TNF-α and IL-6 were profoundly expressed in experimental rats, whereas resveratrol decreases the immunopositivity of TNF-α and IL-6 and restored the altered architectural structure of challenged hepatic tissue. Resveratrol also protects liver cells by suppressing oxidative stress and apoptosis

Connecting Fisher information to bulk entanglement in holography

In the context of relating AdS/CFT to quantum information theory, we propose a holographic dual of Fisher information metric for mixed states in the boundary field theory. This amounts to a holographic measure for the distance between two mixed quantum states. For a spherical subregion in the boundary we show that this is related to a particularly regularized volume enclosed by the Ryu-Takayanagi surface. We further argue that the quantum correction to the proposed Fisher information metric is related to the quantum correction to the boundary entanglement entropy. We discuss consequences of this connection

Whole-genome characterization of human group C rotaviruses: identification of two lineages in the VP3 gene

Group C rotavirus (GCRV) is distributed worldwide as an enteric pathogen in humans and animals. However, to date, whole-genome sequences are available only for a human strain (Bristol) and a porcine strain (Cowden). To investigate the genetic diversity of human GCRVs, nearly full-length sequences of all 11 RNA segments were determined for human GCRVs detected recently in India (v508), Bangladesh (BS347), China (Wu82 and YNR001) and Japan (OH567 and BK0830) and analysed phylogenetically with sequence data for GCRVs published previously. All the RNA segments of human GCRV strains except for the VP3 gene showed high levels of conservation (>93 % nucleotide sequence identity, >92 % amino acid sequence identity), belonging to a single genetic cluster distinct from those of animal GCRVs. In contrast, the VP3 genes of human GCRVs could be discriminated into two clusters, designated M2 and M3, that were distinguished phylogenetically from those of porcine and bovine GCRVs (clusters M1 and M4, respectively). Between M2 and M3, amino acid sequence identity of the VP3 gene was 84.1–84.7 %, whereas high identities were observed within each cluster (92.3–97.6 % for M2, 98.2–99.3 % for M3). Sequence divergence among the four VP3 clusters was observed throughout the amino acid sequence except for conserved motifs, including those possibly related to enzyme functions of VP3. The presence of obvious genetic diversity only in the VP3 gene among human GCRVs suggested that either the M2 or M3 VP3 gene of human GCRVs might have been derived through reassortment from an animal GCRV or from an unidentified human GCRV strain belonging to a novel genogroup

Enhancing livelihoods in farming communities through super-resolution agromet advisories using advanced digital agriculture technologies

Agricultural production in India is highly vulnerable to climate change. Transformational change to farming systems is required to cope with this changing climate to maintain food security, and ensure farming to remain economically viable. The south Asian rice-fallow systems occupying 22.3 million ha with about 88% in India, mostly (82%) concentrated in the eastern states, are under threat. These systems currently provide economic and food security for about 11 million people, but only achieve 50% of their yield potential. Improvement in productivity is possible through efficient utilization of these fallow lands. The relatively low production occurs because of sub-optimal water and nutrient management strategies. Historically, the Agro-met advisory service has assisted farmers and disseminated information at a district-level for all the states. In some instances, Agro-met delivers advice at the block level also, but in general, farmers use to follow the district level advice and develop an appropriate management plan like land preparation, sowing, irrigation timing, harvesting etc. The advisories are generated through the District Agrometeorology Unit (DAMU) and Krishi Vigyan Kendra (KVK) network, that consider medium-range weather forecast. Unfortunately, these forecasts advisories are general and broad in nature for a given district and do not scale down to the individual field or farm. Farmers must make complex crop management decisions with limited or generalised information. The lack of fine scale information creates uncertainty for farmers, who then develop risk-averse management strategies that reduce productivity. It is unrealistic to expect the Agro-met advisory service to deliver bespoke information to every farmer and to every field simply with the help of Kilometre-scale weather forecast. New technologies must be embraced to address the emerging crises in food security and economic prosperity. Despite these problems, Agro-met has been successful. New digital technologies have emerged though, and these digital technologies should become part of the Agro-met arsenal to deliver valuable information directly to the farmers at the field scale. The Agro-met service is poised to embrace and deliver new interventions through technology cross-sections such as satellite remote sensing, drone-based survey, mobile based data collection systems, IoT based sensors, using insights derived from a hybridisation of crop and AIML (Artificial Intelligence and Machine Learning) models. These technological advancements will generate fine-scale static and dynamic Agro-met information on cultivated lands, that can be delivered through Application Programming Interface (APIs) and farmers facing applications. We believe investment in this technology, that delivers information directly to the farmers, can reverse the yield gap, and address the negative impacts of a changing climate