Incompatibility of Observables as State-Independent Bound of Uncertainty Relations

For a pair of observables, they are called "incompatible", if and only if the commutator between them does not vanish, which represents one of the key features in quantum mechanics. The question is, how can we characterize the incompatibility among three or more observables? Here we explore one possible route towards this goal through Heisenberg's uncertainty relations, which impose fundamental constraints on the measurement precisions for incompatible observables. Specifically, we quantify the incompatibility by the optimal state-independent bounds of additive variance-based uncertainty relations. In this way, the degree of incompatibility becomes an intrinsic property among the operators, but not on the quantum state. To justify our case, we focus on the incompatibility of spin systems. For an arbitrary setting of two or three linearly-independent Pauli-spin operators, the incompatibility is analytically solved, the spins are maximally incompatible if and only if they are orthogonal to each other. On the other hand, the measure of incompatibility represents a versatile tool for applications such as testing entanglement of bipartite states, and EPR-steering criteria.Comment: Comments are welcom

Uspostava sendvič ELISE testa za goveđi plazma PON-1 i njegova prediktivna vrijednost za masnu jetru u mliječnih krava

The aim of this study to improve the clinical diagnosis of fatty livers (FL) in dairy cows by using the paraoxonase-1 (PON-1) enzyme as a detection index. Prokaryotic expression technology was used to generate recombinant bovine PON-1 protein. Mice were immunized with this protein to generate hybridoma cells, stably secreting anti-PON-1. Cells were injected into the peritoneal cavity of mice, and ascites were purified to generate bovine PON-1 monoclonal antibody. Rabbits were then immunized with this antigen, and a polyclonal antibody against bovine PON-1 was obtained. Using monoclonal and polyclonal antibodies, a double-antibody sandwich ELISA for plasma PON-1 was constructed. Plasma samples were collected from healthy (n = 13) and FL (n = 13) cows, and plasma PON-1 levels were detected using the PON-1 ELISA. Receiver operating characteristic curve (ROC) analysis was used to analyze correlations between PON-1 levels and FL. Results showed that the ideal working concentration of the monoclonal antibody was 0.8 mg/mL, and the quantitative detection limit was 90 ng/mL. Plasma PON-1 levels were significantly lower in FL cows, when compared with healthy animals. It is concluded that PON-1 ELISA predicts risk factors for dairy cows with FL. PON-1 levels in plasma can be used as an early warning indicator for FL and concentration of 61.87 nmol/L was identified as warning index.Cilj ovog rada bio je unaprijediti kliničku dijagnostiku masne jetre (FL) u mliječnih krava upotrebom enzima paraoksonaze-1 (PON-1) kao indeksa za otkrivanje bolesti. Primijenjena je metoda prokariotske ekspresije kako bi se proizveo rekombinantni goveđi protein PON-1. Miševi su imunizirani ovim proteinom kako bi porizveli stanice hibridoma sa stabilnim izlučivanjem anti-PON-1. Stanice su injektirane u peritonealnu šupljinu miševa te je ascites pročišćen kako bi proizveo goveđa monoklonska protutijela PON-1. Tim su antigenom imunizirani kunići te je dobiveno poliklonsko antitijelo na goveđi PON-1. Upotrebom monoklonskih i poliklonskih antitijela uspostavljen je sendvič ELISA test dva sloja antitijela za plazmatski PON-1. Uzorci plazme prikupljeni su iz zdravih krava (n = 13) i krava s masnom jetrom (n = 13), dok su razine plazmatskog PON-1 detektirane upotrebom PON-1 ELISA. Analizom ROC krivulje analizirane su korelacije između razina PON-1 i FL-a. Rezultati pokazuju da je idealna radna koncentracija monoklonskih protutijela bila 0,8 mg/mL, a kvantitativno ograničenje detekcije 90 ng/mL. Razine plazmatskog PON-1 bile su znakovito niže u krava s masnom jetrom u usporedbi sa zdravim životinjama. Zaključeno je da je PON-1 dobiven ELISA-om prediktor rizičnih čimbenika za masnu jetru u krava. Plazmatske razine PON-1 mogu poslužiti kao rani pokazatelj masne jetre, a kao upozoravajući indeks pokazala se koncentracija od 61,87 nmol/L

Causes and classification of EMD mode mixing

At present, the lack of insight into the problem of mode mixing in Empirical Mode Decomposition (EMD) hinders the development of solutions to the problem. Starting with the phenomenon that the EMD decomposition cannot be accomplished when the number of signal extrema is abnormal, the causes of mode mixing were investigated and the conclusion was reached that there are only two basic types of mode mixing. In light of this finding, the mechanisms of the three typical mode mixing solutions and their limitations were analyzed. It was found from the analysis process and results that the findings of this study regarding the causes and types of mode mixing were correct

Alioth: A Machine Learning Based Interference-Aware Performance Monitor for Multi-Tenancy Applications in Public Cloud

Multi-tenancy in public clouds may lead to co-location interference on shared resources, which possibly results in performance degradation of cloud applications. Cloud providers want to know when such events happen and how serious the degradation is, to perform interference-aware migrations and alleviate the problem. However, virtual machines (VM) in Infrastructure-as-a-Service public clouds are black-boxes to providers, where application-level performance information cannot be acquired. This makes performance monitoring intensely challenging as cloud providers can only rely on low-level metrics such as CPU usage and hardware counters. We propose a novel machine learning framework, Alioth, to monitor the performance degradation of cloud applications. To feed the data-hungry models, we first elaborate interference generators and conduct comprehensive co-location experiments on a testbed to build Alioth-dataset which reflects the complexity and dynamicity in real-world scenarios. Then we construct Alioth by (1) augmenting features via recovering low-level metrics under no interference using denoising auto-encoders, (2) devising a transfer learning model based on domain adaptation neural network to make models generalize on test cases unseen in offline training, and (3) developing a SHAP explainer to automate feature selection and enhance model interpretability. Experiments show that Alioth achieves an average mean absolute error of 5.29% offline and 10.8% when testing on applications unseen in the training stage, outperforming the baseline methods. Alioth is also robust in signaling quality-of-service violation under dynamicity. Finally, we demonstrate a possible application of Alioth's interpretability, providing insights to benefit the decision-making of cloud operators. The dataset and code of Alioth have been released on GitHub.Comment: Accepted by 2023 IEEE International Parallel & Distributed Processing Symposium (IPDPS

Comprehensive comparison of molecular portraits between cell lines and tumors in breast cancer

Background: Proper cell models for breast cancer primary tumors have long been the focal point in the cancer’s research. The genomic comparison between cell lines and tumors can investigate the similarity and dissimilarity and help to select right cell model to mimic tumor tissues to properly evaluate the drug reaction in vitro. In this paper, a comprehensive comparison in copy number variation (CNV), mutation, mRNA expression and protein expression between 68 breast cancer cell lines and 1375 primary breast tumors is conducted and presented. Results: Using whole genome expression arrays, strong correlations were observed between cells and tumors. PAM50 gene expression differentiated them into four major breast cancer subtypes: Luminal A and B, HER2amp, and Basal-like in both cells and tumors partially. Genomic CNVs patterns were observed between tumors and cells across chromosomes in general. High C > T and C > G trans-version rates were observed in both cells and tumors, while the cells had slightly higher somatic mutation rates than tumors. Clustering analysis on protein expression data can reasonably recover the breast cancer subtypes in cell lines and tumors. Although the drug-targeted proteins ER/PR and interesting mTOR/GSK3/TS2/PDK1/ER_P118 cluster had shown the consistent patterns between cells and tumor, low protein-based correlations were observed between cells and tumors. The expression consistency of mRNA verse protein between cell line and tumors reaches 0.7076. These important drug targets in breast cancer, ESR1, PGR, HER2, EGFR and AR have a high similarity in mRNA and protein variation in both tumors and cell lines. GATA3 and RP56KB1 are two promising drug targets for breast cancer. A total score developed from the four correlations among four molecular profiles suggests that cell lines, BT483, T47D and MDAMB453 have the highest similarity with tumors. Conclusions: The integrated data from across these multiple platforms demonstrates the existence of the similarity and dissimilarity of molecular features between breast cancer tumors and cell lines. The cell lines only mirror some but not all of the molecular properties of primary tumors. The study results add more evidence in selecting cell line models for breast cancer research

Injectable Nano-Network for Glucose-Mediated Insulin Delivery

Diabetes mellitus, a disorder of glucose regulation, is a global burden affecting 366 million people across the world. An artificial “closed-loop” system able to mimic pancreas activity and release insulin in response to glucose level changes has the potential to improve patient compliance and health. Herein we develop a glucose-mediated release strategy for the self-regulated delivery of insulin using an injectable and acid-degradable polymeric network. Formed by electrostatic interaction between oppositely charged dextran nanoparticles loaded with insulin and glucose-specific enzymes, the nanocomposite-based porous architecture can be dissociated and subsequently release insulin in a hyperglycemic state through the catalytic conversion of glucose into gluconic acid. In vitro insulin release can be modulated in a pulsatile profile in response to glucose concentrations. In vivo studies validated that these formulations provided improved glucose control in type 1 diabetic mice subcutaneously administered with a degradable nano-network. A single injection of the developed nano-network facilitated stabilization of the blood glucose levels in the normoglycemic state (\u3c200 mg/dL) for up to 10 days

Povezanost negativne energetske bilance (NEB) s energetskim metabolizmom, proizvodnjom mlijeka i reprodukcijskom sposobnošću mliječnih krava tijekom rane laktacije u pokrajini Heilongjiang, Kina

Negative energy balance (NEB) causes economic losses to dairy farms around the globe. The aim of this study was to investigate the effect of NEB on energy metabolism, reproduction, etc. during early lactation in dairy cows on intensive farms in Heilongjiang, China. According to β-hydroxybutyric acid (BHBA), glucose (GLU), Non-esterified fatty acid (NEFA) levels, and clinical manifestations 14-21 days postpartum, 118 cows were divided into a positive energy balance (PEB) group (BHBA2.8, NEFA1.2, GLU0.7 mmol/L, n=51). These indicators were analyzed by cross-sectional research methods combined with Pearson correlation analysis and a prospective cohort study. The results showed that at 14-21 days postpartum, compared with the PEB, the body condition score, body condition loss (BCL), milk urea nitrogen, BHBA, NEFA, the interval from calving to first estrus (ICFE), pregnancy per artificial insemination (P/AI), and calving interval were higher (P2,8, NEFA1,2, GLU0,7 mmol/L; n=51). Navedeni pokazatelji analizirani su kombinacijom metoda presječnog istraživanja, Pearson-ovog koeficijenta korelacije i prospektivnog kohortnog istraživanja. Rezultati su pokazali da je 14-21 dan nakon porođaja skupina NEB u usporedbi sa skupinom PEB imala višu ocjenu tjelesne kondicije, veći gubitak tjelesne kondicije (BCL), te veće vrijednosti za dušik iz ureje mlijeka, BHBA, NEFA, interval od teljenja do prvog estrusa (ICFE), graviditete po umjetnoj oplodnji (P/AI) i interval između teljenja (P<0,05), a niže vrijednosti zadnevnu proizvodnju mlijeka (DL), mliječni protein, GLU, stopu pojave estrusa i stopu koncepcije. Gubitak tjelesne kondicije (BCL) je bio pozitivno povezan s ICFE i P/AI (P<0,05) i negativno povezan sa stopom pojave estrusa te stopom koncepcije (P<0,05). Dnevna proizvodnja mlijeka (DL) pokazala je negativnu povezanost s P/AI (P<0,05). Uočena je pozitivna povezanost NEB-a i anestrusa (2M-H = 12,63, P = 0,0004), a rizik od anestrusa uzrokovanih NEB povećan je 3,67 puta u odnosu na PEB. Zaključci su pokazali da je NEB usko povezan s BCL, što je čimbenik koji utječe na snižavanje proizvodnje mlijeka i reprodukciju mliječnih krava. Osim toga, NEB se pokazao i kao čimbenik rizika za anestrus u mliječnih krava