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Nevin Manimala Statistics

Hybrid photon-phonon blockade

Sci Rep. 2022 Oct 21;12(1):17655. doi: 10.1038/s41598-022-21267-4.

ABSTRACT

We describe a novel type of blockade in a hybrid mode generated by linear coupling of photonic and phononic modes. We refer to this effect as hybrid photon-phonon blockade and show how it can be generated and detected in a driven nonlinear optomechanical superconducting system. Thus, we study boson-number correlations in the photon, phonon, and hybrid modes in linearly coupled microwave and mechanical resonators with a superconducting qubit inserted in one of them. We find such system parameters for which we observe eight types of different combinations of either blockade or tunnelling effects (defined via the sub- and super-Poissonian statistics, respectively) for photons, phonons, and hybrid bosons. In particular, we find that the hybrid photon-phonon blockade can be generated by mixing the photonic and phononic modes which do not exhibit blockade.

PMID:36271120 | DOI:10.1038/s41598-022-21267-4

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Nevin Manimala Statistics

U(1) dynamics in neuronal activities

Sci Rep. 2022 Oct 21;12(1):17629. doi: 10.1038/s41598-022-22526-0.

ABSTRACT

Neurons convert external stimuli into action potentials, or spikes, and encode the contained information into the biological nervous system. Despite the complexity of neurons and the synaptic interactions in between, rate models are often adapted to describe neural encoding with modest success. However, it is not clear whether the firing rate, the reciprocal of the time interval between spikes, is sufficient to capture the essential features for the neuronal dynamics. Going beyond the usual relaxation dynamics in Ginzburg-Landau theory for statistical systems, we propose that neural activities can be captured by the U(1) dynamics, integrating the action potential and the “phase” of the neuron together. The gain function of the Hodgkin-Huxley neuron and the corresponding dynamical phase transitions can be described within the U(1) neuron framework. In addition, the phase dependence of the synaptic interactions is illustrated and the mapping to the Kinouchi-Copelli neuron is established. It suggests that the U(1) neuron is the minimal model for single-neuron activities and serves as the building block of the neuronal network for information processing.

PMID:36271115 | DOI:10.1038/s41598-022-22526-0

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Nevin Manimala Statistics

Multiparameter optimization system with DCNN in precision agriculture for advanced irrigation planning and scheduling based on soil moisture estimation

Environ Monit Assess. 2022 Oct 22;195(1):13. doi: 10.1007/s10661-022-10529-3.

ABSTRACT

Agriculture is a distinct sector of a country’s economy. In recent years, new patterns have evolved in the agricultural industry. In conjunction with sensor scaling down and precision agriculture, the field of remote sensor networks, such as the wireless sensor network (WSN), was developed. Its major purpose is to make horticultural operations simpler to identify, assess, and manage. This paper uses the proposed DCNN to predict soil moisture and plan irrigation for precision agriculture farmers to reduce water consumption used for cultivation and increase production yield by comparing water content during various stages of plant growth and integrating IoT applications into agriculture. It also optimizes the water level for future irrigation decisions to maintain crop growth and water stability. The data must be served and stored in the form of a grid view, according to Apriori and GRU (gated recurrent unit). Using numerous sensor and parameter modelling methodologies, this system assists in the prediction of irrigation planning based on irrigation needs. The predicted parameters include soil moisture, temperature, and humidity. This observed experimental data supports smart irrigation in crop production with a high yield and little water use. DCNN has a 98.5% experimental result accuracy rate and the MSE value is predicted in DCNN 99.25% of the time.

PMID:36271063 | DOI:10.1007/s10661-022-10529-3

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Nevin Manimala Statistics

Ambulatory sleeve gastrectomy: a prospective feasibility and comparative study of early postoperative morbidity

Surg Endosc. 2022 Oct 21. doi: 10.1007/s00464-022-09721-w. Online ahead of print.

ABSTRACT

BACKGROUND: Given its short procedure time and low morbidity, there is enthusiasm to perform sleeve gastrectomy (SG) in an outpatient setting. However, most relevant studies include an overnight stay at a medical facility (≤ 24-h). Hence, we investigated the feasibility and safety of a same-day discharge (SDD) protocol for laparoscopic SG.

METHODS: In a prospective pilot study (02/01/2021-02/28/2022), all patients planned for SG were screened for eligibility. Patients met the inclusion criteria if they were ≤ 65 years old, without major comorbidity, and lived close to the hospital. Postoperatively, patients who met discharge criteria were sent home directly from the recovery room. Patients were called the same night and the next morning. Feasibility was defined as discharge on the day of surgery without emergency department (ED) visit or readmission within 24-h. Secondary outcomes, including 90-day morbidity, were compared to patients who met inclusion criteria but chose a same-day admission (SDA) approach during the same study period. Descriptive statistics are displayed as count (percentage) and median (interquartile range).

RESULTS: A total of 320 patients were planned for SG during the study period, 229 of whom met eligibility criteria and underwent SG with 56 agreeing to SDD-SG while 173 opted for SDA-SG. Baseline characteristics were all similar between both groups except for obstructive sleep apnea being more prevalent in SDA-SG group (38.2% vs. 16.1%; P < 0.001). Operative characteristics including procedure time were similar between both groups. Successful SDD-SG was achieved in 54(96%) of patients with a median of 6.0(1.0) hours of stay in the recovery room. Ninety-day morbidity was similar between SDD-SG and SDA-SG groups (1.8% vs. 6.9%, respectively; P = 0.196).

CONCLUSION: A SDD protocol for laparoscopic SG was feasible and safe in selected patients. Larger studies that evaluate patient reported outcomes and include bypass-type procedures may be needed to guide safe use of ambulatory bariatric surgery.

PMID:36271061 | DOI:10.1007/s00464-022-09721-w

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Nevin Manimala Statistics

A machine learning approach to explore predictors of graft detachment following posterior lamellar keratoplasty: a nationwide registry study

Sci Rep. 2022 Oct 21;12(1):17705. doi: 10.1038/s41598-022-22223-y.

ABSTRACT

Machine learning can be used to explore the complex multifactorial patterns underlying postsurgical graft detachment after endothelial corneal transplantation surgery and to evaluate the marginal effect of various practice pattern modulations. We included all posterior lamellar keratoplasty procedures recorded in the Dutch Cornea Transplant Registry from 2015 through 2018 and collected the center-specific practice patterns using a questionnaire. All available data regarding the donor, recipient, surgery, and practice pattern, were coded into 91 factors that might be associated with the occurrence of a graft detachment. In this research, we used three machine learning methods; a regularized logistic regression (lasso), classification tree analysis (CTA), and random forest classification (RFC), to select the most predictive subset of variables for graft detachment. A total of 3647 transplants were included in our analysis and the overall prevalence of graft detachment was 9.9%. In an independent test set the area under the curve for the lasso, CTA, and RFC was 0.70, 0.65, and 0.72, respectively. Identified risk factors included: a Descemet membrane endothelial keratoplasty procedure, prior graft failure, and the use of sulfur hexafluoride gas. Factors with a reduced risk included: performing combined procedures, using pre-cut donor tissue, and a pre-operative laser iridotomy. These results can help surgeons to review their practice patterns and generate hypotheses for empirical research regarding the origins of graft detachments.

PMID:36271020 | DOI:10.1038/s41598-022-22223-y

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Nevin Manimala Statistics

The distance distribution of human microRNAs in MirGeneDB database

Sci Rep. 2022 Oct 21;12(1):17696. doi: 10.1038/s41598-022-22253-6.

ABSTRACT

MicroRNAs (miRNAs) are small single-stranded non-coding RNAs around 22 nucleotide lengths found in organisms, playing an important role in cell differentiation, development, gene regulation, and apoptosis. The distance of disease miRNA biomarkers has been used to explore the association between various diseases as well as the association between virus and disease in the literature. To date, there have been no studies on deriving the distribution of the pairwise distance of human miRNAs. As the pairwise distance of miRNA biomarkers might be a useful tool in studying the disease association, in this paper, the distance distributions of human miRNAs were derived such that they could be used to measure the closeness between miRNAs. Two distance models were used to calculate the pairwise distances of 567 Homo sapiens miRNA genes accessed from the MirGeneDB database. These miRNA pairwise distances were fitted by the normal distribution, gamma distribution, empirical cumulative distribution, and the kernel density estimation method. This is the first study to provide the distance distribution of human miRNAs. The similarity of miRNA biomarkers for several diseases was examined using the derived distributions.

PMID:36271017 | DOI:10.1038/s41598-022-22253-6

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Nevin Manimala Statistics

Isolation and characterization of bacteriophage Ib_pec2 against shigatoxigenic Escherichia coli

J Basic Microbiol. 2022 Oct 21. doi: 10.1002/jobm.202200398. Online ahead of print.

ABSTRACT

This study was aimed to isolate and characterize bacteriophage against drug-resistant, shigatoxigenic Escherichia coli (STEC), one of the zoonotic, food-borne organisms associated with ruminants, mainly cattle. STEC were isolated (n = 35) from neonatal calves, dairy workers, and the surrounding environment and their antimicrobial resistance pattern was studied. Out of the 35 isolates tested, 17 isolates were found to be multidrug resistant to important antibiotics like ampicillin, amoxicillin-clavulanate, ciprofloxacin, streptomycin, and tetracycline. Bacteriophage namely Ib_pec2 was isolated against one of the STEC isolates and its morphology, genetic and proteomic characterization was done. Morphological analysis by TEM revealed bacteriophages belonging to myoviridae family. The genetic characterization of g23 gene revealed that the bacteriophage belonged to Tequatrovirus of myoviridae family. Proteomic analysis was able to identify five proteins identical to Tequatrovirus of myoviridae family. One-step growth curve experiment revealed a latency period of 40 min and a burst size of 893 pfu/bacteria. Temperature and pH ranging from 40°C to 50°C, pH 6-8, respectively. Phage could able to lyse majority of the STEC isolates. STEC are commensal organisms in the gastrointestinal tract of ruminants but are pathogenic in humans. Bacteriophages can be used as alternatives to antibiotics to control bacterial growth in ruminants and prevent its further spillage in the environment.

PMID:36270976 | DOI:10.1002/jobm.202200398

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Nevin Manimala Statistics

Exploring environmenATL justice and data analytics in an environmental studies lab course

Ecol Appl. 2022 Oct 21:e2769. doi: 10.1002/eap.2769. Online ahead of print.

ABSTRACT

The environmental studies laboratory is an exciting place where students investigate, analyze, and reflect. Students test and apply theories and make abstract concepts concrete. As an example, ecology and environmental science are increasingly using ‘big data’ to expand and refine research questions. This commentary reflects on the design and integration of an environmental justice and data analytics module in an environmental studies lab course. The module introduces an environmental justice framework to give students an understanding of tools and strategies to engage, assess, and intervene at multiple levels; while also developing advocacy and communication skills. Poor and minority populations have historically borne the brunt of environmental inequalities in the United States, suffering disproportionally from the effects of pollution, resource depletion, dangerous jobs, limited access to common resources, and exposure to environmental hazards. Paying particular attention to ‘redlining’ and the ways that race, ethnicity, class and gender have shaped the political and economic dimensions of environmental injustices, this module challenges students to critically examine redlining, socioeconomic, and environmental factors in Atlanta, GA (USA) to develop and explore research questions that may visually and/or statistically illuminate trends, patterns and processes of environmenATL justice. This module also introduces some of the basic data handling and data analysis skills that give students an understanding of data types, descriptive statistics, sampling, and basic inferential statistics. By intentionally incorporating environmental justice activities and conversations in the classroom, instructors afford students an opportunity to engage in authentic examination of their world and make positive changes. Many of the skills learned and knowledge gained in this activity are directly transferable to post-baccalaureate studies (e.g. graduate school, medical school, professional training etc.) and the world of employment. The module can also be adapted to various curriculum, courses, and communities. This article is protected by copyright. All rights reserved.

PMID:36270975 | DOI:10.1002/eap.2769

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Nevin Manimala Statistics

Evaluation of h-index in Academic Interventional Radiology

Acad Radiol. 2022 Oct 18:S1076-6332(22)00511-6. doi: 10.1016/j.acra.2022.09.020. Online ahead of print.

ABSTRACT

RATIONALE AND OBJECTIVE: This study evaluates the association of h-index, a widely used bibliometric factor used to determine promotions and grant allocations, with academic ranking, sex, and geographic distribution in the interventional radiology community.

MATERIALS AND METHODS: A database of all academic interventional radiologists in the US was created; academic rank, sex, institution, and geographic location were obtained. The Scopus database was used to determine the physicians’ h-index.

RESULTS: Our query identified 832 board-certified interventional radiologists. The mean h-index amongst all interventional radiologists was 10.81 ± 13.17 (median, 7; range, 0-167). H-indices were significantly different amongst assistant professors, associate professors, and professors (p < 0.0001). Our query identified 724 male interventional radiologists and 108 female interventional radiologists. The mean h-index amongst male interventional radiologists was 11.27 ± 13.69 (median, 7; range, 0-167) and amongst female interventional radiologists was 7.72 ± 8.33 (median, 5; range, 0-47). When stratified by rank, there was no statistically significant difference in h-index between male and female interventional radiologists. Multiple regression analysis identified sex is not significantly associated with h-index, but academic rank and region are.

CONCLUSION: H-index in academic interventional radiology correlates significantly with faculty position and may be a factor in determining academic promotion. The sex-based differences in h-index seem to be due to the greater number of male faculty in senior academic positions who have been in the field for longer.

PMID:36270964 | DOI:10.1016/j.acra.2022.09.020

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Nevin Manimala Statistics

AHPBA senior leaders’ assessments of strengths, weaknesses, opportunities, and threats facing fellowship training in HPB surgery: “We need to standardize our training experiences”

HPB (Oxford). 2022 Oct 1:S1365-182X(22)01604-5. doi: 10.1016/j.hpb.2022.09.014. Online ahead of print.

ABSTRACT

BACKGROUND: Multiple fellowship programs in North America prepare surgeons for a career in Hepato-Pancreatico-Biliary (HPB) surgery. Inconsistent operative experiences and disease process exposures across programs and pathways produces variability in training product and therefore, lack of clarity around what trained HPB surgeons are prepared to do in early practice. Thus, a strengths, weaknesses, opportunities, and threats (SWOT) analysis of AHPBA fellowship training was conducted.

METHODS: This was a mixed-methods, cross-sectional study. Eleven AHPBA-Founding Members (FM) and 24 current or former Program Directors (PD) of programs eligible for AHPBA certificates were surveyed and interviewed. Grounded theory principles and thematic network analysis were used to analyze interview transcripts. Descriptive statistics were used to analyze survey data.

RESULTS: Three main themes were identified: (i) Concern for training rigor and consistency (ii) Desire to standardize curricula and broaden training requirements and, (iii) Need to validate both the value of training and job marketability via certification.

DISCUSSION: Based on the themes identified, the strengths of AHPBA-certified HPB programs include superior technical training and case volumes. Areas of improvement included elevating baseline competencies by increasing required case volume and breadth to ensure minimally invasive experience, operative autonomy, and multidisciplinary care coordination.

PMID:36270938 | DOI:10.1016/j.hpb.2022.09.014