Human 3D Avatar Modeling with Implicit Neural Representation: A Brief Survey

A human 3D avatar is one of the important elements in the metaverse, and the modeling effect directly affects people's visual experience. However, the human body has a complex topology and diverse details, so it is often expensive, time-consuming, and laborious to build a satisfactory model. Recent studies have proposed a novel method, implicit neural representation, which is a continuous representation method and can describe objects with arbitrary topology at arbitrary resolution. Researchers have applied implicit neural representation to human 3D avatar modeling and obtained more excellent results than traditional methods. This paper comprehensively reviews the application of implicit neural representation in human body modeling. First, we introduce three implicit representations of occupancy field, SDF, and NeRF, and make a classification of the literature investigated in this paper. Then the application of implicit modeling methods in the body, hand, and head are compared and analyzed respectively. Finally, we point out the shortcomings of current work and provide available suggestions for researchers.Comment: A Brief Surve

Actively implementing an evidence-based feeding guideline for critically ill patients (NEED): a multicenter, cluster-randomized, controlled trial

Background: Previous cluster-randomized controlled trials evaluating the impact of implementing evidence-based guidelines for nutrition therapy in critical illness do not consistently demonstrate patient benefits. A large-scale, sufficiently powered study is therefore warranted to ascertain the effects of guideline implementation on patient-centered outcomes. Methods: We conducted a multicenter, cluster-randomized, parallel-controlled trial in intensive care units (ICUs) across China. We developed an evidence-based feeding guideline. ICUs randomly allocated to the guideline group formed a local "intervention team", which actively implemented the guideline using standardized educational materials, a graphical feeding protocol, and live online education outreach meetings conducted by members of the study management committee. ICUs assigned to the control group remained unaware of the guideline content. All ICUs enrolled patients who were expected to stay in the ICU longer than seven days. The primary outcome was all-cause mortality within 28 days of enrollment. Results: Forty-eight ICUs were randomized to the guideline group and 49 to the control group. From March 2018 to July 2019, the guideline ICUs enrolled 1399 patients, and the control ICUs enrolled 1373 patients. Implementation of the guideline resulted in significantly earlier EN initiation (1.20 vs. 1.55 mean days to initiation of EN; difference − 0.40 [95% CI − 0.71 to − 0.09]; P = 0.01) and delayed PN initiation (1.29 vs. 0.80 mean days to start of PN; difference 1.06 [95% CI 0.44 to 1.67]; P = 0.001). There was no significant difference in 28-day mortality (14.2% vs. 15.2%; difference − 1.6% [95% CI − 4.3% to 1.2%]; P = 0.42) between groups. Conclusions: In this large-scale, multicenter trial, active implementation of an evidence-based feeding guideline reduced the time to commencement of EN and overall PN use but did not translate to a reduction in mortality from critical illness. Trial registration: ISRCTN, ISRCTN12233792. Registered November 20th, 2017

Actively implementing an evidence-based feeding guideline for critically ill patients (NEED): a multicenter, cluster-randomized, controlled trial.

BackgroundPrevious cluster-randomized controlled trials evaluating the impact of implementing evidence-based guidelines for nutrition therapy in critical illness do not consistently demonstrate patient benefits. A large-scale, sufficiently powered study is therefore warranted to ascertain the effects of guideline implementation on patient-centered outcomes.MethodsWe conducted a multicenter, cluster-randomized, parallel-controlled trial in intensive care units (ICUs) across China. We developed an evidence-based feeding guideline. ICUs randomly allocated to the guideline group formed a local "intervention team", which actively implemented the guideline using standardized educational materials, a graphical feeding protocol, and live online education outreach meetings conducted by members of the study management committee. ICUs assigned to the control group remained unaware of the guideline content. All ICUs enrolled patients who were expected to stay in the ICU longer than seven days. The primary outcome was all-cause mortality within 28 days of enrollment.ResultsForty-eight ICUs were randomized to the guideline group and 49 to the control group. From March 2018 to July 2019, the guideline ICUs enrolled 1399 patients, and the control ICUs enrolled 1373 patients. Implementation of the guideline resulted in significantly earlier EN initiation (1.20 vs. 1.55 mean days to initiation of EN; difference - 0.40 [95% CI - 0.71 to - 0.09]; P = 0.01) and delayed PN initiation (1.29 vs. 0.80 mean days to start of PN; difference 1.06 [95% CI 0.44 to 1.67]; P = 0.001). There was no significant difference in 28-day mortality (14.2% vs. 15.2%; difference - 1.6% [95% CI - 4.3% to 1.2%]; P = 0.42) between groups.ConclusionsIn this large-scale, multicenter trial, active implementation of an evidence-based feeding guideline reduced the time to commencement of EN and overall PN use but did not translate to a reduction in mortality from critical illness.Trial registrationISRCTN, ISRCTN12233792 . Registered November 20th, 2017

Actively implementing an evidence-based feeding guideline for critically ill patients (NEED): a multicenter, cluster-randomized, controlled trial (vol 26, 46, 2022)

BackgroundPrevious cluster-randomized controlled trials evaluating the impact of implementing evidence-based guidelines for nutrition therapy in critical illness do not consistently demonstrate patient benefits. A large-scale, sufficiently powered study is therefore warranted to ascertain the effects of guideline implementation on patient-centered outcomes.MethodsWe conducted a multicenter, cluster-randomized, parallel-controlled trial in intensive care units (ICUs) across China. We developed an evidence-based feeding guideline. ICUs randomly allocated to the guideline group formed a local "intervention team", which actively implemented the guideline using standardized educational materials, a graphical feeding protocol, and live online education outreach meetings conducted by members of the study management committee. ICUs assigned to the control group remained unaware of the guideline content. All ICUs enrolled patients who were expected to stay in the ICU longer than seven days. The primary outcome was all-cause mortality within 28 days of enrollment.ResultsForty-eight ICUs were randomized to the guideline group and 49 to the control group. From March 2018 to July 2019, the guideline ICUs enrolled 1399 patients, and the control ICUs enrolled 1373 patients. Implementation of the guideline resulted in significantly earlier EN initiation (1.20 vs. 1.55 mean days to initiation of EN; difference - 0.40 [95% CI - 0.71 to - 0.09]; P = 0.01) and delayed PN initiation (1.29 vs. 0.80 mean days to start of PN; difference 1.06 [95% CI 0.44 to 1.67]; P = 0.001). There was no significant difference in 28-day mortality (14.2% vs. 15.2%; difference - 1.6% [95% CI - 4.3% to 1.2%]; P = 0.42) between groups.ConclusionsIn this large-scale, multicenter trial, active implementation of an evidence-based feeding guideline reduced the time to commencement of EN and overall PN use but did not translate to a reduction in mortality from critical illness.Trial registrationISRCTN, ISRCTN12233792 . Registered November 20th, 2017

Two metallothionein genes in Oxya chinensis: molecular characteristics, expression patterns and roles in heavy metal stress.

Metallothioneins (MTs) are small, cysteine-rich, heavy metal-binding proteins involved in metal homeostasis and detoxification in living organisms. In the present study, we cloned two MT genes (OcMT1 and OcMT2) from Oxya chinensis, analyzed the expression patterns of the OcMT transcripts in different tissues and at varying developmental stages using real-time quantitative PCR (RT-qPCR), evaluated the functions of these two MTs using RNAi and recombinant proteins in an E. coli expression system. The full-length cDNAs of OcMT1 and OcMT2 encoded 40 and 64 amino acid residues, respectively. We found Cys-Cys, Cys-X-Cys and Cys-X-Y-Z-Cys motifs in OcMT1 and OcMT2. These motifs might serve as primary chelating sites, as in other organisms. These characteristics suggest that OcMT1 and OcMT2 may be involved in heavy metal detoxification by capturing the metals. Two OcMT were expressed at all developmental stages, and the highest levels were found in the eggs. Both transcripts were expressed in all eleven tissues examined, with the highest levels observed in the brain and optic lobes, followed by the fat body. The expression of OcMT2 was also relatively high in the ovaries. The functions of OcMT1 and OcMT2 were explored using RNA interference (RNAi) and different concentrations and treatment times for the three heavy metals. Our results indicated that mortality increased significantly from 8.5% to 16.7%, and this increase was both time- and dose-dependent. To evaluate the abilities of these two MT proteins to confer heavy metal tolerance to E. coli, the bacterial cells were transformed with pET-28a plasmids containing the OcMT genes. The optical densities of both the MT-expressing and control cells decreased with increasing concentrations of CdCl2. Nevertheless, the survival rates of the MT-overexpressing cells were higher than those of the controls. Our results suggest that these two genes play important roles in heavy metal detoxification in O. chinensis

Groundwater Nitrate Contamination and Driving Forces from Intensive Cropland in the North China Plain

High nitrate in groundwater is a serious problem especially in highly active agricultural areas. In this paper, the concentration and spatial distribution of groundwater nitrate in cropland area in the North China Plain were assessed by statistical and geostatistical techniques. Nitrate concentration in groundwater reached a maximum of 526.58 mg/L, and 47.2%, 21.33% and 11.13% of samples had levels in excess of nitrate safety threshold concentration (50 mg/L) in shallow, middle-deep and deep groundwater, respectively. And NO3- content significantly decreased with groundwater depth. Groundwater nitrate concentrations under vegetable area are significantly higher than ones under grain and orchard. And there are great differences in spatial distribution of nitrate in the North China Plain and pollution hotspot areas are mainly in Shandong Province. Based on both multiple regressions combined with principal component analysis (PCA), significant variables for nitrate variation in three types of ground water were found: population per unit area, percentage of vegetable area, percentage of grain crop area, livestock per unit area, annual precipitation and annual mean temperature for shallow groundwater; population per unit area and percentage of vegetable area for middle-deep groundwater; percentage of vegetable area, percentage of grain crop area and livestock per unit area for deep groundwater

Cadmium tolerance of <i>E. coli</i> BL21 cells expressing <i>OcMT1</i> and <i>OcMT2</i>.

<p>A: OcMT1, B: OcMT2. Bacterial growth curve of <i>E. coli</i> cells transformed with pET-28a, pET-28a-OcMT and pET-28a-OcMT-IPTG. pET-28a is an “empty” vector; pET-28a-OcMT group is transformed with the <i>OcMT1</i> or <i>OcMT2</i> gene without IPTG; pET-28a-OcMT-IPTG group is transformed with the <i>OcMT1</i> or <i>OcMT2</i> gene with IPTG. Five microliters of CdCl₂ was added into medium when bacteria were grown to OD600 = 0.6. All bacteria were grown for 11 h. Concentration gradient of CdCl₂ were 0, 0.82, 1.74, 3.27 mM.</p

SDS-PAGE analysis of His and two His-OcMT fusion proteins expressed in <i>E. coli</i> BL21 (DE3) cells.

<p>Protein samples were separated by 15% SDS-PAGE and stained with Coomassie brilliant blue. Lane 1, medium range molecular weight marker; Lane 2, <i>E. coli</i> BL21 with pET-28a-OcMT2 cell lysate induced with IPTG; Lane 3, <i>E. coli</i> BL21 with pET-28a-OcMT2 without IPTG; Lane 4, <i>E. coli</i> BL21 with pET-28a; Lane 5, <i>E. coli</i> BL21 with pET-28a-OcMT1 cell lysate induced with IPTG; Lane 6, <i>E. coli</i> BL21 with pET-28a-OcMT1 without IPTG induction.</p