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Intraoral scanning has benefits over conventional impression making, but whether scanning is sufficiently accurate for multiple implants is unclear.The purpose of this in vitro study was to compare the trueness of digital scans acquired by using intraoral scanners from a small range to a complete arch with the conventional impression technique and to determine the influence of 2 different evaluation methods (best-fit algorithm versus absolute linear deviation) on the outcomes of accuracy assessment.A mandibular model with 8 implants (A-H) around an edentulous arch was used as the master model. Open-format standard tessellation language (STL) data sets (1 reference file from a highly accurate dental laboratory scanner, 10 files from an intraoral scanner, and 10 files from digitized conventional impressions at room temperature) were imported to a metrology software program, and 5 groups of scanning ranges (AB, FGH, CDEF, BCDEFG, and ABCDEFGH) were identified simulating different clinical situations. Two evaluation methods-root mean square values calculated from the best-fit algorithm and average value of linear discrepancies from absolute linear deviation-were used to describe the trueness values. The impacts of different scanning or impression methods, ranges, and evaluation methods were tested by using a 3-way ANOVA. The effect of the scanning range on accuracy was further identified with 1-way ANOVA. The paired-sample t test was used to determine the differences of trueness values between the 2 methods in different groups.The trueness values of the implant impressions were significantly affected by different scanning or impression methods (P.001), evaluation methods (P.001), and scanning ranges (P.001) as independent variables. With use of the best-fit algorithm, deviations from the digital scans were significantly greater than those from the conventional impressions in cross-arch situations (groups CDEF, BCDEFG, and ABCDEFGH). With use of the absolute linear deviation method, statistically significant lower accuracy was found when larger areas were encountered (groups BCDEFG and ABCDEFGH). Use of the absolute linear deviation method resulted in a higher mean score of inaccuracy than that from the best-fit algorithm method in most situations.Scanning or impression methods, ranges, and evaluation methods affected the dimensional accuracy (trueness) of scans or impressions with multiple implants. Digital scans had worse trueness values compared with those made with the conventional splinting open-tray technique when cross-arch implant impressions were acquired.

Aimed at complex distributed no-fly zones avoidance problems, a novel adaptive lateral reentry guidance algorithm is proposed. Firstly, by introducing the improved attractive and repulsive potential fields, an improved artificial potential field method is developed. Combined with the proposed judgment criterion for whether a no-fly zone has been avoided, the proposed improved artificial potential field method effectively solves the reference heading angle determination problem under the constraints of complex distributed no-fly zones. Then, based on the proposed no-fly zone’s threat quantitative evaluation method and the reference heading angle determined by the proposed improved artificial potential field method, the heading corridor is improved to increase its sensitivity to the threat changes of the no-fly zones. Finally, for satisfying the requirements of complex distributed no-fly zones avoidance, a novel guidance logic via improved heading corridor is proposed to update the reference heading corridor adaptively in real time according to the threat and constraint changes of the no-fly zones, and the bank reversal logic is employed to control the lateral motion. The simulation results for nominal and dispersed cases indicate that the proposed guidance algorithm has high robustness, stability, and applicability, and is feasible and effective to deal with the complex distributed no-fly zones avoidance problems.

The recent Food and Agricultural Organization/World Health Organization/United Nations University expert consultations on protein requirements and quality have emphasized the need for the new Digestible Indispensable Amino Acid Score (DIAAS), as a measure of protein quality. This requires human measurements of the true ileal digestibility of individual indispensable amino acids (IAA) until the end of the small intestine. Digestibility is measured using standard oro-ileal balance methods, which can only be achieved by an invasive naso-ileal intubation in healthy participants or fistulation at the terminal ileum. Significant efforts have been made in last two decades to develop non-invasive or minimally invasive methods to measure IAA digestibility in humans. The application of intrinsically labeled (with stable isotopes like 13C, 15N and 2H) dietary proteins have helped in circumventing the invasive oro-ileal balance techniques and allowed for the differentiation between endo and exogenous protein digestibility. The non-invasive indicator amino acid oxidation (IAAO) technique, which is routinely employed to measure IAA requirements, has been modified to estimate metabolic availability (a sum of digestibility and utilization) of IAA in foods, but provide estimate for a single IAA at a time and burdensome for participants. The recently developed minimally invasive dual isotope tracer method measures small intestinal digestibility of multiple amino acids at once and is suitable for use in vulnerable groups and disease conditions. However, it remains to be validated against standard oro-ileal balance techniques. This review critically evaluates and compares the currently available stable isotope-based protein quality evaluation methods with a focus on the digestibility and metabolic availability measurements in humans. In the view of building reliable DIAAS database of various protein sources and subsequently supporting protein content claims in food labeling, a re-evaluation and harmonization of the available methods are necessary.

In studies that assessed the accuracy of implant surgical guides, evaluations were based on the placement position of the implant by using a manufactured surgical guide. However, such assessments could involve errors that may occur during implant placement. Therefore, evaluating the 3-dimensional accuracy of the fabrication of the implant surgical guide itself is not enough. In the evaluation method described in this article, location-related information is obtained by connecting a scan body to the sleeve of the surgical guide instead of directly placing the implant. This helps to evaluate the accuracy of the surgical guide without errors in the placement of an implant.

Nowadays, several news portals, government websites, and social media sites are generating a massive amount of digitalized Hindi textual information. Stopword removal is a significant factor in text mining tasks that helps the miner to enhance the performance of a system. This paper attempts to construct the corpus specific stopwords lists for Hindi text documents using statistical and knowledge-based methods. In order to prepare the stopwords list, the proposed method considers the ranking of the words given by different methods followed by normalization of the outcomes of these methods using the social choice theory based vote ranking method. Further, we propose an evaluation method to evaluate the prepared stopword lists and investigate their behavior using text mining models. We also compare our prepared stopword lists with the baselines and conclude that the technique which fetches the best features does not necessarily identify the candidate stop words. To the best of our knowledge, the proposed approach guarantees the removal of candidate stop words and has the least information dissipation.

Objective The purpose of this study was to compare surgical outcomes for obstructive sleep apnea (OSA) when the procedure was based on the results of drug-induced sleep endoscopy (DISE) vs. the awake Müller's maneuver (MM). Methods Forty-seven patients with OSA who underwent sleep surgery were included. Patients were divided into 2 groups according to their preoperative upper airway evaluation method. Twenty-five patients received only MM for surgical decision making (MM group), and 22 patients received both MM and DISE (DISE group) for surgical decision making. Results The surgical success rate of the DISE group was higher than that of the MM group (59% vs. 36%), but the difference was not significant (p = 0.118). The differences between pre- and postoperative apnea-hypopnea index (AHI) values in both the MM and DISE group were highly significantly different (p 0.001). Fifteen patients in the DISE group (68.2%) received multi-level surgery, while in the MM group only 7 patients (28%) received multi-level surgery. Patients with more severe OSA (AHI 22 or lowest O2 saturation 81%) had better surgical outcomes when their surgical procedures were based on the findings of DISE, rather than those of MM. Conclusion The results indicate that DISE provides no benefits with respect to surgical outcomes for patients with mild to moderate OSA; however, for patients with more severe OSA surgical procedures based on DISE result in better outcomes.

Objective The Yamamoto–Kohama criteria are clinically useful for determining the mode of tumor invasion, especially in Japan. However, this evaluation method is based on subjective visual findings and has led to significant differences in determinations between evaluators and facilities. In this retrospective study, we aimed to develop an automatic method of determining the mode of invasion based on the processing of digital medical images. Study Design Using 101 digitized photographic images of anonymized stained specimen slides, we created a classifier that allowed clinicians to introduce feature values and subjected the cases to machine learning using a random forest approach. We then compared the Yamamoto–Kohama grades (1, 2, 3, 4C, 4D) determined by a human oral and maxillofacial surgeon with those determined using the machine learning approach. Results The input of multiple test images into the newly created classifier yielded an overall F-measure value of 87%, (Grade 1: 93%, Grade 2: 67%, Grade 3: 89%, Grade 4C: 83%, Grade 4D: 94%). These results suggest that the output of the classifier was very similar to the judgments of the clinician. Conclusions This system may be valuable for diagnostic support to provide an accurate determination of the mode of invasion.

Previous studies have shown that the fatigue life distribution of metal materials fabricated with Additive Manufacturing (AM) methods, such as Direct Energy Deposited (DED) Ti-6.5Al-2Zr-1Mo-1V alloys, exhibits two peaks. To promote the application of AM in aerospace and other engineering fields, developing a fatigue strength evaluation method suitable for AM materials based on their unique fatigue behaviours and fatigue life distributions is necessary. In this paper, a novel Detail Fatigue Rating (DFR) method was developed to evaluate the fatigue strength of DED Ti-6.5Al-2Zr-1Mo-1V based on a bimodal Weibull distribution and the excessive restriction on the allowable stress of potential was improved. Meanwhile, a Bimodal Weibull distribution model for fatigue life and its parameter estimation method were established based on a two-parameter Weibull distribution. The fatigue life at a specific reliability level and confidence level was calculated by using the bootstrap method. The calculation results showed that fatigue life estimated by using the bimodal Weibull distribution at the high reliability level and high confidence level is higher than that estimated by using the two-parameter Weibull distribution. Furthermore, The S-N curve at the specified confidence level and reliability level was fitted.

Tectona grandis L.f is a timber plant that is commonly referred to as teak. Its wide use as a medicine in the various indigenous systems makes it a plant of importance. A wide gamut of phytoconstituents like alkaloids, phenolic glycosides, steroids, etc. has been reported. A renewed interest in this plant has resulted in scientific investigations by various researchers towards the isolation and identification of active constituents along with scientific proof of its biological activities. The different parts of the plant have been scientifically evaluated for their antioxidant, antipyretic, analgesic, hypoglycemic, wound healing, cytotoxic, and many more biological activities. Documentation of this scientific knowledge is of importance to have consolidated precise information encompassing the various aspects of this plant, which could provide a base for future studies. This review is a compilation of the salient reports on these investigations concerning phytochemistry, the methods used to identify and quantify the constituents, the evaluation methods of the biological activity, toxicological studies, allergies and the patent/patent applications. This will further help researchers to find an area of the gap for future studies.

As the complexity of flight missions continues to increase, sending a timely warning or providing assistance to pilots helps to reduce the probability of operational errors and flight accidents. Monitoring pilots’ physiological data, real-time evaluation of mission load is a feasible technical way to achieve this. In this paper, a set of flight tasks including aircraft control, human-computer interaction and mental arithmetic tests are designed to simulate five mission loads at different flight difficulty levels. A sensitivity analysis method based on a comprehensive test is proposed to select a set of sensitive physiological factors. Then, based on the SVM hierarchical combination classification method, the pilot mission load real-time evaluation model is established. The test results show significant differences in EMG, respiration rate (abdomen), heart rate, blood oxygen saturation, pupil area, fixation duration, number of fixations, and saccades. The high accuracy obtained from experiments proved that the proposed real-time evaluation model is applicable to meet the requirements of real working environments. The findings can provide methodological references for mission load evaluation research in other fields.

Remote Collaboration mediated by Mixed and Augmented Reality (MR/AR) shows great potential in scenarios where physically distributed collaborators need to establish a common ground to achieve a shared goal. So far, most research efforts have been devoted to creating the enabling technology, overcoming engineering hurdles and proposing methods to support its design and development. To contribute to more in-depth knowledge on how remote collaboration occurs through these technologies, it is paramount to understand where the field stands and how characterization and evaluation have been conducted. In this vein, this work reports the results of a literature review which shows that evaluation is frequently performed in ad-hoc manners, i.e., disregarding adapting the evaluation methods to collaborative AR. Most studies rely on single-user methods, which are not suitable for collaborative solutions, falling short of retrieving the necessary amount of contextualized data for more comprehensive evaluations. This suggests minimal support of existing frameworks and a lack of theories and guidelines to guide the characterization of the collaborative process using AR. Then, a critical analysis is presented in which we discuss the maturity of the field and a roadmap of important research actions is proposed, that may help address how to improve the characterization and evaluation of the collaboration process moving forward and, in consequence, improve MR/AR based remote collaboration.

Dry powder inhalers (DPIs) had been widely used in lung diseases on account of direct pulmonary delivery, good drug stability and satisfactory patient compliance. However, an indistinct understanding of pulmonary delivery processes (PDPs) hindered the development of DPIs. Most current evaluation methods explored the PDPs with over-simplified models, leading to uncompleted investigations of the whole or partial PDPs. In the present research, an innovative modular process analysis platform (MPAP) was applied to investigate the detailed mechanisms of each PDP of DPIs with different carrier particle sizes (CPS). The MPAP was composed of a laser particle size analyzer, an inhaler device, an artificial throat and a pre-separator, to investigate the fluidization and dispersion, transportation, detachment and deposition process of DPIs. The release profiles of drug, drug aggregation and carrier were monitored in real-time. The influence of CPS on PDPs and corresponding mechanisms were explored. The powder properties of the carriers were investigated by the optical profiler and Freeman Technology four powder rheometer. The next generation impactor was employed to explore the aerosolization performance of DPIs. The novel MPAP was successfully applied in exploring the comprehensive mechanism of PDPs, which had enormous potential to be used to investigate and develop DPIs., Graphical abstract An innovative modular process analysis platform composed of a laser particle size analyzer and changeable modules was successfully applied to investigate the detail mechanism of pulmonary delivery processes of DPIs with different carrier particle sizes.Image 1

Objective The development and evaluation of new employees in air medical transport has historically lacked standardization and competency-based learning goals. Here we discuss the development, implementation, and assessment of a new competency-based education and evaluation method at Geisinger's Life Flight air medical transport service. Methods Using Bloom's taxonomy of learning, 14 competencies for flight employees were identified. An electronic database was created to track progress across competencies and serve as an information repository for the identification of goals and the development of individualized learning plans. Ten months after implementation of the new method, 11 preceptors and education team members were surveyed to understand their views on the new program. Results At the time of survey administration, 20 orientees had completed orientation under the new education and evaluation program in an average of 6.45 weeks, with a range of 3 to 10 weeks. Of the 11 surveyed instructors, 81.1% definitely agree that the new method adequately assesses performance compared with 45.5% with the previous unstandardized method; 81.8% of the instructors rated the overall change as very helpful. Conclusion The adoption of a competency-based learning model for air medical transport employee education and evaluation improves the assessment of performance and allows for the development of customized learning plans.

Introduction Large-animal models such as sheep for facial nerve regeneration research have not yet been established because of the lack of methods for assessing the electrophysiological function of regenerated nerves. In this study, we developed a percutaneous measurement method for the evoked compound muscle action potential (CMAP) of the facial nerve in sheep. Methods Six 3-year-old castrated male Corriedale sheep were used in this study. Under general anesthesia, an anatomical exploration was performed to identify the course of the buccal branch of the facial nerve and its innervating muscles on one side, followed by the application of surface stimulating electrodes to the contralateral side of the face along the course of the buccal branch of the facial nerve to obtain CMAP measurements of the nasolabial levator muscle. Results Percutaneous CMAP measurements of the nasolabial levator muscle could be obtained in all animals by placing stimulating electrodes 1 cm apart on the line coinciding with the course of the buccal branch of the facial nerve revealed by the preceding anatomical exploration. Mean values for electrophysiological parameters were amplitude 4.7 ± 0.7 mV, duration 2.1 ± 0.6 ms, and latency 3.6 ± 0.4 ms. Conclusion We have established a percutaneous measurement method for CMAP of the buccal branch of the facial nerve in sheep. This method is expected to be very useful in future studies of facial nerve regeneration for long nerve defects in sheep., Highlights • A percutaneous CMAP measurement method for the ovine facial nerve was established. • Anatomical experiment demonstrated the method's physiological accuracy. • The ovine facial nerve enables a more realistic model of facial nerve regeneration.

Conventional ex-ante evaluations rely on a mix of economic, environmental, and social indicators to assess the potential impacts of Genetically Modified (GM) crops prior to their commercial release. While these predictive studies have produced useful knowledge, they have also consistently overestimated the ex-post outcomes of GM crops for African smallholder farmers. Yet these same assessment methods remain the dominant approach to project farmer outcomes for a new suite of soon-to-be commercialized GM staple crops. The research presented in this paper offers a different evaluative approach for these new GM crops by taking inspiration from farming systems research (FSR). We use the conceptual starting point of FSR scholarship—the farming system—to conduct an exploratory predictive analysis of three GM crops currently in the experimental pipeline: Water Efficient Maize for Africa (WEMA) in Kenya, disease-resistant matooke banana in Uganda, and Bt cowpea in Burkina Faso. Our findings suggest that the lofty projected benefits of these crops are unlikely to be realized by many, if not most, smallholder farmers due to incongruences with the farming systems they are designed to benefit. This research demonstrates the importance of using farming system-based evaluation methods to better anticipate likely farm-level outcomes of new breeding technologies.

With a history spanning thousands of years, the water system of Suzhou is an indispensable carrier of urban space and civil culture. Quantificational model analysis of the waterfront in the ancient city of Suzhou has significant implications for the future design of waterfront space and the establishment of an evaluation method to determine the vitality of such space. In this study, a vitality evaluation model was first constructed using river attributes, the spatial type of waterfront areas, vision accessibility, transportation accessibility, and combined new data extracted using spatial factor analysis. Second, a vitality evaluation matrix was established using the analytic hierarchy process to simulate the vitality of waterfront spaces. Third, a hash algorithm was employed to determine the fitting degree between the vitality model of Suzhou's waterfront space and crowd activity. The different areas between them were found and then the factor evaluation process was adjusted on this basis of analyzing the causes. Thus, this study identified the factors influencing the vitality of Suzhou's waterfront. Furthermore, this research constructed a model for evaluating the vitality of waterfront spaces. Finally, some guidelines were presented regarding the design and implementation of waterfront spaces in urban design.

With the increasing demand for environmental protection, CO2, as a natural refrigerant, has always been environmentally friendly and safe, which makes transcritical CO2 heat pump system attract more attention. The internal heat exchanger is employed to improve the performance of transcritical CO2 heat pump system to match the traditional heat pump circulation system. In this work, two evaluation methods are proposed, one is the actual operation thermal effectiveness of internal heat exchanger, the other is the actual increase rate of COP. Compared with the experimental results, the conclusions can be extracted that the actual increase rate of COP can effectively evaluate the impact of the internal heat exchanger on system performance. In addition, this research deeply analyzes the influence of the internal heat exchanger on exergy efficiency. The results show that the internal heat exchanger greatly reduces the exergy efficiency under the discharge pressure of 7310 kPa and the ambient temperature of 15 °C, and the difference value between the system with and without internal heat exchanger reaches 39%. However, the influence of the internal heat exchanger on exergy efficiency decreases with the increase of discharge pressure and ambient temperature, the minimum difference value is only 0.1% at 11000 kPa and 30 °C.

The X-ray computed tomography system (XCT) as a coordinate measuring system has been increasingly introduced into the manufacturing industry because of its capability of measuring internal features. However, the metrological performance evaluation method for XCT has not yet been standardized. One of the biggest reasons of this is the difficulty in evaluating the material influence. The previous research by the authors revealed that the material influence significantly affects the form of the object to be measured. ISO/TC 213/WG 10, which covers the ISO standards of coordinate measuring machines, proposes the introduction of an additional object, called an “obstructive body,” by which the material influence is enhanced. This study presents the experimental results and a software simulation, in which the material influence is produced in a specific area and not on the entire surface of the test object. Additionally, requirements for the obstructive body in the industrial standardization of performance evaluation methods for XCT are proposed.

The estimated ultimate recovery (EUR) of shale gas wells is influenced by many factors, and the accurate prediction still faces certain challenges. As an artificial intelligence algorithm, deep learning yields notable advantages in nonlinear regression. Therefore, it is feasible to predict the EUR of shale gas wells based on a deep-learning algorithm. In this paper, according to geological evaluation data, hydraulic fracturing data, production data and EUR evaluation results of 282 wells in the WY shale gas field, a deep-learning-based algorithm for EUR evaluation of shale gas wells was designed and realized. First, the existing EUR evaluation methods of shale gas wells and the deep feedforward neural network algorithm was systematically analyzed. Second, the technical process of a deep-learning-based algorithm for EUR prediction of shale gas wells was designed. Finally, by means of real data obtained from the WY shale gas field, several different cases were applied to testify the validity and accuracy of the proposed approach. The results show that the EUR prediction with high accuracy. In addition, the results are affected by the variety and number of input parameters, the network structure and hyperparameters. The proposed approach can be extended to other shale fields using the similar technic process.

Surfactant-enhanced water spray technology, one of the most economical and efficient dust suppression technologies, is widely used for dust control in mining. Unfortunately, current research on this technology appears to be scattered, and the results do not provide an effective approach for coal dust control. Aimed at addressing this problem by critically reviewing coal dust agglomeration mechanisms and dust suppression effectiveness, this review summarized four steps for droplets capturing coal dust, and two agglomeration mechanisms(immersion and distribution mechanisms) are illustrated based on them. In addition, the dust suppression effect is categorized as either indirect dust suppression or direct dust suppression, depending on the coal dust removal effect. The suppression results show that surfactants can significantly improve the indirect dust suppression, the direct dust suppression efficiency of surfactant-enhanced water spray technology is generally between 80 % and 95 % and can be increased by approximately 40 % compared to the conventional spray dust reduction efficiency, and the suppression efficiency for respirable coal dust (below PM10) is approximately 1 % lower than that of total dust. In the discussion on the challenges and further research directions, relative motion and capture of fine particles, effect evaluation methods and standard, relationship between direct and indirect dust suppression effects, as well as field application technology, are suggested as the main challenges and directions for improving the efficiency of this technology.

Objectives The aim of this study was to determine Relapse and TMD as postoperative complication in skeletal class III patients undergoing bimaxillary orthognathic surgery. Materials and methods Data was obtained by database searching using The Cochrane Central Register of Controlled Trials (central), PUBMED, SCOPUS, EMBASE, Google scholar, National Medical library, New Delhi. The titles and abstracts of the electronic search results were screened and evaluated by two observers for eligibility according to the inclusion and exclusion criteria. Results 5261 articles were retrieved for the review. Among these, 3474 duplicate articles were removed. 418 studies were selected based on the eligibility criteria. For the present review, 30 articles were included after elimination according to the inclusion criteria. The Prisma diagram flowchart demonstrates our selection scheme. Quality assessment criteria to evaluate the studies were decided by two review authors in accordance with CONSORT guidelines. Each study was assessed using the evaluation method described in the Cochrane Handbook for Systematic Reviews. Among the 30 studies included in the review, marked degree of relapse in the mandible was noted from 3 months - 1 year postoperatively in 8 studies, 5 studies reported both TMD prevalence and relapse, whereas only 4 studies reported TMD disorder alone. Conclusion Complications of relapse and TMD are associated with bimaxillary orthognathic surgery procedures. More RCTs and CCTs are needed in this regard to get better quality evidence. This review was registered with PROSPERO: CRD42020211342.

Although total mesorectal excision (TME) is regarded as a standard procedure for rectal cancer, technical definition and evaluation method have not yet been investigated for intersphincteric resection (ISR). This study was performed to introduce a complete ISR procedure, and to assess whether total intersphincteric longitudinal muscle excision (TILME) facilitated the completeness of ISR and reduced recurrence.A total of 1080 patients with rectal adenocarcinoma who underwent robot-assisted low anterior resection (LAR) over 10 years were consecutively enrolled. Propensity-score matching of the two LAR groups (ISR vs LAR group, 1:1) and three ISR subgroups (partial vs subtotal vs total ISR subgroup, 2:2:1) was performed by strict adjustment of baseline characteristics. Archived specimens and video-/photo-records were reevaluated to examine completeness of TILME.Complete-TILME was performed in 84.5% of patients who underwent ISR. Multivariate analysis showed that incomplete-TILME was the only parameter independently associated with increased 5-year cumulative local recurrence (odds ratio = 23.385; 95% confidence interval = 1.492-366.421; p = 0.03), and that incomplete-TILME was independently associated with adipose tissue surrounding the intersphincteric longitudinal muscle, coloanal anastomosis, and total ISR (p 0.001-0.05). Although mean incontinence scores and anorectal manometry deteriorated to some degree 12-24 months after surgery in all patients, they remained acceptable. The 5-year cumulative DFS (74.1% vs 60%, p = 0.18) and OS (85.9% vs 70%, p = 0.10) rates tended to be higher in patients with complete than incomplete-TILME.The completeness of TILME appears to be an independent indicator of complete ISR, reducing local recurrence following lower rectal cancer surgery.

There is abundant literature about the impact of residential insulation on energy consumption using different methods. However, ex-post evaluation methods have not been used yet, which are helpful when the participants in a program are not chosen randomly. Therefore, this study performs the first ex-post evaluation of a residential insulation program using the “matching with differences-in-differences” method. This non-experimental method allows obtaining the causal impact of the program since it controls for observable factors and non-observable factors that are invariable over time. The data comes from a unique survey that includes energy consumption for heating and control variables for households benefited and not benefited by the program, both in the year before and after the retrofit. The results show that the residential insulation program does not significantly reduce energy consumption or external PM2.5 emissions in the treated dwellings. Still, there is a significant increase in the perception of thermal comfort associated with the rebound effect. Thus, it is concluded that the program has not been an effective tool to reduce air pollution, but it improves the quality of life through an increase in thermal comfort.

Natural polymers such as protein and polysaccharide belong to the basic kinds of food soft mater. With great diversity and complexity, the intermolecular assembly structure formed by these polymers can form stable co soluble complexes or have phase separation according to components compatibility and assembly structure stability, which are of vital importance for the further development of food science and industry. This article introduces the compatibility and various assembly structures of soft matter components and the various interactions between polysaccharides and proteins and their impact on microstructure, and summarizes the existing methods for characterizing compatibility of food soft matter and the stability of assembly structure.

In this paper, we assess the lightweight efficiency of the realistic 3D model data through comparative tests by introducing the realistic three-dimensional model into building information modeling (BIM) design. To meet the varied needs of engineering design in the construction field at different stages, a quality evaluation method for the lightweight realistic 3D model is proposed, with the texture quality and plane positioning accuracy of the model taken into account. The results show that the best lightweight coefficient of realistic 3D model data in film box (FBX) format is 40%. Under a lightweight coefficient at 40%, the amount of model data is reduced by 25%, with only small holes incurred in the texture, and the atness error is ± 9 mm. After lightweight processing, the model meets the requirements of BIM designers for vision and plane positioning accuracy. By putting forward a data lightweight processing standard and a model evaluation method based on the idea of BIM design, we aimed to solve the challenges in applying realistic 3D models to BIM design due to the large amounts of data, thereby to lay a foundation for wider application of realistic 3D models to BIM design.

Robot-assisted bonnet polishing systems (RABPSs) have been widely studied in order to expand the application of bonnet polishing technology. Currently, low working stiffness is one of the most important problems that needs to be solved for RABPSs. To address this issue, an evaluation method for the working stiffness of RABPSs should be studied. Therefore, a theoretical and experimental study is presented in this paper. First, the static stiffness model of the RABPS was built based on the Denavit–Hartenberg (D–H) method and the compliance matrix. Subsequently, the force characteristics of the RABPS during the bonnet polishing process were analyzed. Next, by combining the above static stiffness model and the force analysis results, a new index, that is, the normal stiffness coefficient (NSC), was proposed to evaluate the working stiffness of the RABPS. Finally, the performance of the NSC of the RABPS was verified by simulation and experiment. Both results show that the NSC has higher accuracy than other commonly used indexes when it is used to describe the working stiffness of RABPSs. This research provides an important theoretical foundation for the optimization of the working stiffness of RABPSs for future studies.

Lean systems which provide the elimination of waste and increase productivity in both manufacturing and service systems are highly desired by the companies. Designing a lean system requires enormous amount of efforts and is time consuming unless the right steps are followed. The first step of lean implementation is the assessment of leanness which determines the status quo of the existing system with respect to leanness. In searching of a comprehensive evaluation method, this study aims to propose a leanness assessment methodology which is able to aid company’s lean transformation. This study mainly differs from the existing studies by taking into account a wide range of lean indicators with a comprehensively designed questionnaire and evaluating leanness via neutrosophic DEMATEL (The Decision Making Trial and Evaluation Laboratory) based scoring structure. The proposed methodology is applied in three companies. Moreover, sensitivity analysis concerning metrics and comparison with classic DEMATEL are performed.

The extrusion load on casing in ultra-deep well is uncertain, which limits the application of safety factor method. Therefore, the evaluation method of collapsing safety and reliability on casing during drilling in ultra-deep wells is put forward. Based on the extrusion load model in ultra-deep well considering the diversity of strength parameters of casing and the integrity of formation-cement sheath-casing system, the uncertainty distribution functions of collapse strength and extrusion load on casing are derived by introducing probability and statistics theory. Then, the theory of "stress-strength interference" is applied to obtain the reliability R, confidence interval and reliability-safety factor nR of casing. Taking multiple ultra-deep wells in the Kuqa block of the Tarim Oilfield as an example, the collapse safety and reliability analysis on casing is carried out. Several conclusions are made based on the oilfield statistics. The traditional safety factor is greater than the reliability-safety factor. The surface casing and the production casing are both safer than the technical casing. More accurate original data can narrow the confidence interval width of nR and reduce the collapse risk of technical casing. The change in reliability is consistent with the change of the reliability-safety factor. For technical casing, when R is greater than 0.50 and 0.92, nR is greater than 1.0 and 1.1 respectively. For production casing, when R is greater than 0.98, nR is greater than 1.1. For each type of casing, affected by the uncertainty of the extrusion load on casing, when the extrusion load exceeds a certain value (but this value is less than the casing strength), the reliability begins to decrease. The larger the standard deviation of extrusion load is, the more obvious the influence on reliability change will be. Compared with the traditional design safety factor, the change of the anti-collapse safety degree of the casing can be more intuitively displayed by the reliability, which could provide an important supplement for the selection of traditional design safety factor during drilling operations.

Background Active packaging plays an important role in food and seafood preservation in the sector of food safety. The main role of antimicrobial packaging is to prohibit the bacterial and fungal growth. Biopolymers are the main film-forming materials which can be integrated with preservatives and antimicrobial agents, and the edible films containing the additives can be utilized as a substitute to maintain food products. Scope and approach Although different tests including disc and well diffusion assays, viable cell counts, vapor-phase technique, and optical density-based methods are used by microbiologists, no standard methodology has been firmly established to assess the antimicrobial effects of edible films. Hence, this review discusses the strengths and limitations of the published microbial methodologies used for assessing the activity of antimicrobial packaging. Key findings and conclusion The type of active components and materials used to produce edible films are among the most fundamental aspects to select an appropriate evaluation method. Our findings revealed that the disc and well diffusion assays followed by the viable cell count methods are the most common methods for evaluating the antimicrobial activity of edible films.

Objective The purpose of this study was to compare the flexibility of the thoracolumbar fascia (TLF) in individuals with and without subacromial impingement syndrome (SAIS). A secondary purpose was to demonstrate a new method for measuring TLF flexibility. Methods A total of 60 participants—30 diagnosed with SAIS and 30 asymptomatic—were included. In both groups, trunk flexibility was assessed by the modified Schober test, TLF flexibility by rotational measurement on a goniometric platform, and shoulder posterior capsule tightness by tape measurement. The data obtained were compared using t tests for independent variables. Results No statistically significant difference was observed for any parameter between participants with SAIS and healthy controls (P > .05). Conclusion For the participants we studied, the flexibility of the TLF was not associated with SAIS. The goniometric evaluation method used in this study was affordable and feasible. The validity and reliability of this measurement method should be assessed further in future studies.

In 2017, the Brazilian Society of Anesthesiology (SBA) and the National Medical Residency Committee (CNRM) presented a joint competence matrix to train and evaluate physicians specializing in Anesthesiology, which was enforced in 2019. The competency-based curriculum aims to train residents in relation to certain results, in that residents are considered capable when they are able to act in an appropriate and effective manner within certain standards of performance. Canada and the United States (US) also use competency-based curriculum to train their professionals. In Canada, the format is the basis for using an evaluation method known as Entrustable Professional Activities (EPA), in which the mentor assesses residents’ capacity to perform certain tasks, classified in 5 levels. The US, in turn, uses Milestones as evaluation, in which competencies and sub-competencies are assessed according to residents’ progress during training. The present article aims to describe and compare the different competency-based curriculum and the evaluation methods used in the three countries, and proposes a reflection on future paths for medical education in Anesthesiology in Brazil.

In this study, a modal-based structural damage identification method is proposed and applied to a portal beam structure as a case study. A two-stage evaluation method, involving the combination of a residual force vector method and an eigensensitivity method, is proposed to determine the locations of damaged elements in a finite element model. The physical model variables of these elements are then updated using an optimization updating method that detects damage severity. The optimization algorithm to update the model is solved using a sequential quadratic programming method. The severity of the elemental damage is indicated by the final updated physical model variables of the finite element analysis model. The effectiveness of the two-stage evaluation and optimization update methods is verified via comparison of the reference and updated physical model variables through the case study. It is determined that the structural damage detection method with two-stage evaluation and optimization updating developed in this study could be applied for the monitoring and early warning of structural damage.

With the development of Unmanned Aerial Vehicle (UAV) system autonomy, network communication technology and group intelligence theory, mission execution in the form of a UAV swarm will be an important realization of future applications. Traditional single-UAV mission reliability modeling methods have been unable to meet the requirements of UAV swarm mission reliability modeling. Therefore, the UAV swarm mission reliability modeling and evaluation method is proposed. First, aimed at the interdependence among the multiple layers, a multi-layer network model of a UAV swarm is established. At the same time, based on the system having the following characteristics—using a mission chain to complete the mission and applying the connectivity of the mission network—the mission network model of a UAV swarm is established. Second, vulnerability and connectivity are selected as two indicators to reflect the reliability of the mission, and aimed at random attack and deliberate attack, vulnerability and connectivity evaluation methods are proposed. Finally, the validity and accuracy of the constructed model are verified through simulations, and the model and selected indicators can meet the reliability requirements of the UAV swarm mission. In this way, this study provides quantitative reference for UAV-swarm-related decision-making work and supports the development of UAV-swarm-related work.

In this paper, a new evaluation method of reliability and security in cyber-physical system (CPS) considering communication failures is proposed based on instantaneous availability (IA) model and its fluctuation analysis. In this new method, IA model of CPS is established using the M a r k o v process principle, and three types of system states, namely, working state, repairing state and delay-repairing state, are discussed from the perspective of reliability and security. On the basis of the locking error, the numerical solution of the model is solved by the fourth order Runge–Kutta method, and the instantaneous availability of the CPS is proved to be fluctuating. Finally, the impact of different parameters on the instantaneous availability of fluctuations and the ways to suppress fluctuations and improve the CPS reliability are obtained by analyzing the instantaneous availability of different parameters.

While chemical industrial development in China is growing rapidly, the corresponding safety training resources remain inadequate, which may often lead to increased risk of chemical accidents. These accidents are often associated with the negligence of safety management, poor safety hazard awareness, and lack of safety practice. In order to alleviate these prominent risk factors in chemical industries in China, our study develops a talent training model related to chemical process safety. First, we propose an approach for establishing the "talent training model" related to chemical process safety, consisting of three steps: analyzing the current status and existing problems of talent training related to chemical process safety, determining the theoretical basis and training objectives for developing interdisciplinary talents, and designing a new talent training model. Second, we establish a talent training model using the proposed method, which includes a comprehensive curriculum system, a diversified teaching pattern, and a quintuple evaluation method. Furtherly, we determine the expected outcomes of the talent training model. The research results provide an innovative chemical process safety training method that is applicable nationwide, also it works as a reference for other rapidly developing countries in the chemical process industry to improve safety within the chemical industry. (c) 2020 Published by Elsevier B.V. on behalf of Institution of Chemical Engineers.

Aimed at the hot spot of a (photovoltaic) PV system, this research focused on an investigation of the corresponding mitigating strategies. First, the current hot spot mitigating strategies of PV panels were summarized and compared from the aspects of mitigating cost, power loss, hot spot temperature and the output power of PV panels, and then, an intuitive evaluation method to hot spot mitigating strategies was developed on the basis of the area assessment. Then, a new hot spot mitigating strategy was developed by using a divider resistor in series. The mitigating circuit of the proposed strategy was designed, and its operating principle was analyzed. Finally, the effectiveness of the mitigating strategy was verified by simulation and experiments. Compared with the others, the proposed hot spot mitigating strategy had the advantages of lower temperature and larger output power of PV panels. Finally, a potential application of the power loss the on divider resistor was explored in brief and some conclusions were reached.

Declines in PhD enrollment, funding and support for PhD students, and the quality and quantity of the nursing research pipeline has fueled the concern about providing high-quality education in research-focused nursing doctoral programs. To address the challenges and opportunities facing research focused PhD education, the University of Pennsylvania School of Nursing convened an invitational summit, Re-Envisioning Research-Focused PhD Programs of the Future, of research-intensive institutions. Both as a dissemination strategy and as an effort to engage perspectives from other Schools with PhD programs, we presented a summary of the Penn Summit discussion at the AACN Doctoral Education Conference (AACN Doctoral Conference). Focused discussions at both events further identified opportunities for research focused PhD programs, including recruiting undergraduate students, establishing research-focused partnerships, creating clear evaluation methods. AACN Doctoral conference participants also discussed the need to discuss and identify competencies, common subject areas, and financial resources for PhD students and graduates. This synthesis of discussions, considerations, and challenges affecting research-focused doctoral programs of nursing serve as a basis and catalyst for further discussion and action to ensure PhD research focused programs are preparing successful nurse scientists of the future.

For dynamic scheduling, which is daily decision-making in a job-shop, machine availability prediction, disturbance detection and performance evaluation are always common bottlenecks. Previous research efforts on addressing the bottlenecks primarily emphasize on the analysis of data from the physical job-shop, but with little connection and convergence with its virtual models and simulated data. By introducing digital twin (DT), further convergence between physical and virtual spaces of the job-shop can be achieved, which greatly enables dynamic scheduling. DT fuses both real and simulated data to provide more information for the prediction of machine availability on one hand; and on the other hand, it helps to detect disturbances through comparing the physical machine with its continuously updated digital counterpart in real time, triggering timely rescheduling when needed. It also enables comprehensive performance evaluation for rescheduling using multiple-dimension models, which can describe geometric properties, physics parameters and behaviors of the machines. In the paper, a five-dimension DT for a machine in the job-shop is introduced first, then the DT-based machine availability prediction, disturbance detection and performance evaluation methods are explored. Based on this, a DT-enhanced dynamic scheduling methodology is proposed. A scheduling process of making hydraulic valves in a machining job-shop is taken as a case study to illustrate the effectiveness and advantages of the proposed method.

A literature review on the assembly design methodologies (DfA) oriented to the assembly of large and heavy parts, reveals the need to develop a DfA methodology. In addition, the lack of DfA evaluation methods for on-site assembly is also observed. The most widespread DfA methodologies are more oriented toward the improvement of factory assembly processes, where the assembly processes are well defined and standardised. Hence, this article presents a new methodology for the design of assemblies with large and heavy parts on site, called OSIA (On-Site Installation Analysis). OSIA methodology aims to provide data (indicators). On the one hand the theoretical basis of the OSIA methodology is based on three key concepts: i) analysis of assembly operations similar to the one used by the SMED methodology; ii) generic implementation process of DfA methodologies; and, iii) compilation of assembly operation times and estimation of standard times per operation. On the other hand, the steps in the implementation of the methodology are summarized in: i) database development with assembly operations and standard times; ii) assembly operations analysis; iii) calculation of assembly time; and iv) product optimization. In this way, OSIA methodology supports the designer in the specification phase, detailed design phase and in the redesign processes, providing the designer with indicators that make it possible to optimise the design of the parts and reduce the assembly operations of a product on site.

Connectivity evaluation of fracture networks is important in the design, assessment, and development of reservoirs in various engineering applications involving geothermal exploitation and the petroleum industry. By employing nonhomogeneous Poisson distribution and annealing arithmetic, this study generates fracture networks that fit well with actual outcrop fracture data. Based on Allard's definition of the connectivity index, a weighted factor is introduced, and an extended connectivity evaluation method is proposed to consider the effects of the aperture and its correlation with trace length. The results of the analysis show that the extended method improves the accuracy and reliability of connectivity evaluation compared with the traditional method. Moreover, the extended method is effective and accurate at predicting potential preferential flow paths in a practical example of the Dragon and Tiger Mountain (Jiangxi, China), and can better show the anisotropy with a change in the aperture. Hence, the proposed method extends the function of connectivity analysis and can benefit well location optimization in geothermal or petroleum exploration.

The application of helicopter emergency rescue is becoming increasingly widespread, but the flight crew training in this area is still difficult due to high cost and risk. Nevertheless, with the development of Virtual Reality (VR) technology, virtual simulation has become a significant role in crew training of helicopter rescue. During the implementation of VR-based training, how to transform complex real tasks into VR scenarios and how to evaluate the performance of crew are of great importance. To address these issues, a novel VR-based R-E-A-D (Report, Evaluate, Agree, Do) evaluation model for training is proposed, which is suitable for complex missions with multiple tasks, multiple scenarios, and multiple people. Then, a mapping method of VR scenarios is put forward, which can transform the real tasks into virtual scenarios to serve the virtual simulation training. Finally, an experiment is carried out to verify the feasibility of the evaluation method and virtual scenario mapping method.

Introduction: This study aimed to develop an artificial neural network (ANN) model for cervical vertebral maturation (CVM) analysis and validate the model's output with the results of human observers. Methods: A total of 647 lateral cephalograms were selected from patients with 10-30 years of chronological age (mean +/- standard deviation, 15.36 +/- 4.13 years). New software with a decision support system was developed for manual labeling of the dataset. A total of 26 points were marked on each radiograph. The CVM stages were saved on the basis of the final decision of the observer. Fifty-four image features were saved in text format. A new subset of 72 radiographs was created according to the classification result, and these 72 radiographs were visually evaluated by 4 observers. Weighted kappa (w kappa) and Cohen's kappa (c kappa) coefficients and percentage agreement were calculated to evaluate the compatibility of the results. Results: Intraobserver agreement ranges were as follows: w kappa = 0.92-0.98, c kappa = 0.65-0.85, and 70.8%-87.5%. Interobserver agreement ranges were as follows: w kappa = 0.76-0.92, c kappa = 0.4-0.65, and 50%-72.2%. Agreement between the ANN model and observers 1, 2, 3, and 4 were as follows: w kappa = 0.85 (c kappa = 0.52, 59.7%), w kappa = 0.8 (c kappa = 0.4, 50%), w kappa = 0.87 (c kappa = 0.55, 62.5%), and w kappa = 0.91 (c kappa = 0.53, 61.1%), respectively (P < 0.001). An average of 58.3% agreement was observed between the ANN model and the human observers. Conclusions: This study demonstrated that the developed ANN model performed close to, if not better than, human observers in CVM analysis. By generating new algorithms, automatic classification of CVM with artificial intelligence may replace conventional evaluation methods used in the future.

Graphical abstract, Highlights • Data from two different in vitro test methods for the same evaluation subjects were compared. It was investigated whether spine simulators with real human cadavers (SSCs) and finite element models (FEMs) provide the same data exemplarily for range of motion (ROM) before and after insertion of motion-retaining devices. • Only fifty-nine percent of SSC meta-analyses show restored ROM after insertion of the device compared to the intact spinal segment. In FEM meta-analyses, ROM is restored in ninety percent. • Ten percent of ROM analyses show significantly different data between SSCs and FEMs. • With regard to the included studies, data generated by SSCs and FEMs cannot be used unrestricted as alternative and complementary data. • Our analysis provides a new approach to compare data from associated test methods., Background Range-of-motion (ROM) data generated by the in vitro test methods of spine simulators with cadavers (SSCs) and finite element models (FEMs) are used alternatively and complementarily for in vitro evaluations. Aim of Review Our purpose is to compare exemplary segmental ROM data from SSCs and FEMs before and after ball-and-socket total disc replacement (bsTDR) to determine whether the two test methods provide the same data for the same evaluation subjects. Key Scientific Concepts of Review We performed 70 meta-analyses (MAs) and 20 additional comparative analyses based on data from 21 SSC studies used for 39 MAs and 16 FEM studies used for 31 MAs. Only fifty-nine percent (n = 23/39) of SSC MAs show a restored ROM after bsTDR, whereas in FEM MAs, the ROM is restored in ninety percent (n = 28/31). Among the analyses comparing data from the same spinal segments, motion directions and bsTDR, SSC and FEM data are significantly different in ten percent (n = 2/20). According to our results, data generated by SSCs and FEMs cannot be used as alternative and complementary data without restriction. The quality of the evaluation methods itself as well as potential technical reasons for the discrepant results were not our evaluation target. Further SSC and FEM data should be compared using the same approach.

Background In recent years, the antioxidant capacity of plant protein-derived peptides has been depicted in a growing number of studies. Plant proteins have been considered as the new source of antioxidant peptides, which not only save energy but also strengthen treatment of oxidation-related diseases and delay the oxidation of food, thus improve the quality of life. Although reports of the preparation, structure, and activity of antioxidant peptides has increased tremendously and some antioxidant peptides have been commercialized. However, research on antioxidant peptides derived from plant proteins still lacks a systematic review and evaluation. Scope and approach This review summarizes recent advances in plant protein-derived antioxidant peptides, mainly including: (i) Preparation, purification, identification and application of plant protein-derived antioxidant peptides by enzymatic hydrolysis; (ii) Influencing factors, evaluation methods and mechanism of antioxidant protein hydrolysates or peptides; (iii) Future research prospects and existing problems. Key findings and conclusions The conventional purification and identification of antioxidant peptides are expensive and time-consuming. In order to overcome this problem, computer-aided mathematical models (molecular docking, QSAR research, etc.), bioinformatics tools and real-time updated protein databases have been widely explored and studied. In addition, future research should focus on large-scale commercial production of plant protein-derived antioxidant peptides, comprehensive study of structure-activity relationship of antioxidant peptides, deep understanding of antioxidant mechanism, and verification of health benefits in vivo. This review provides a timely reference for the development of new antioxidant peptides in functional foods and nutritional supplements.

In powder metallurgy engineering, the master sintering curve (MSC) is crucial for estimating the mechanical properties of sintered products and optimizing sintering process parameters. A rapid evaluation method, that is, a domain-adversarial neural network, is established in the field of sintering to transfer learning from Al2O3 to SiC, concerning the effect of the heating rate on the sintering densification, in which one material (e.g. SiC) lacks an MSC and the material (e.g. Al2O3) has an overabundance of MSCs. In the unsupervised mode, we can roughly predict the densification evolution of SiC based on the MSC data of Al2O3. In the semi-supervised mode, prediction accuracy gradually increases with the increase of Al2O3 data and approaches a certain upper limit. Compared with the traditional sintering density prediction models, the proposed approach can provide an effective and rapid solution to the problem of data scarcity in the sintering field.

Based on well test interpretation, production performance analysis, overburden permeability and porosity test, gas-water core flooding test and high-pressure mercury injection, a quantitative correlation has been built of in-situ effective permeability with routine permeability and water saturation, and the ranges of Main Flow Channel Index (MFCI) are determined for different permeability levels in porous sand gas reservoirs. A new method to evaluate the in-situ effective permeability of porous sand reservoir and a correlation chart of reserves producing degree and main flow channel index are established. The results reveal that the main flow channel index of porous sand gas reservoirs has close correlation with routine matrix permeability and water saturation. The lower the routine matrix permeability and the higher the water saturation, the lower the MFCI is. If the routine matrix permeability is greater than 5.0×10–3, the MFCI is generally greater than 0.5. When the routine matrix permeability is from 1.0×10–3 to 5.0×10–3, the MFCI is mainly between 0.2 and 0.5. When the routine matrix permeability is less than 1.0×10–3, the MFCI is less than 0.2. The evaluation method of in-situ effective permeability can be used to evaluate newly discovered or not tested porous sand gas reservoirs quickly and identify whether there is tight sand gas. The correlation chart of reserves producing degree and main flow channel index can provide basis for recoverable reserves evaluation and well infilling, and provide technical support for formulation of reasonable technical policy of gas reservoir.

Despite the growing interest of the automotive industry in using recycled polymers, their undesired odor is limiting their application in vehicles' interior components. To get deeper insights into its causes, this study aimed at characterizing the odor of post-consumer and recycled automotive polypropylene with different contents of talc and an anti-fogging additive. Samples were evaluated by different sensory methods currently applied by the automotive industry (GMW 3205 and VDA 270), which confirmed, that they are not feasible for reuse in interior automotive applications. As these odor evaluations are usually performed by non-trained panelists and do not allow a detailed description of the samples' single odor qualities, sensory evaluation according to ISO 13299 was performed by trained panelists. Samples showed medium-high odor intensities rated from 5.1 to 5.6, and a general dislike of the odor with hedonic ratings from 1.8 to 2.6 (scale 0-10). Their odor profiles correlated well with the odorants identified by chemo-analytical characterization using gas chromatography-olfactometry (GC-O) and two-dimensional GC-O coupled with mass spectrometry (2D-GC-MS/O). An array of odorants with benzene and phenolic structures were identified as potential contributors to the samples' overall smell and are likely to originate from degradation of additives commonly used in automotive components. While the addition of talc or anti-fogging additive did not significantly improve the odor of the samples, the description of the samples' smell and the identification of odor-active compounds related to it allow the development of avoidance strategies for the manufacturing of neutral smelling products intended for vehicles' interior applications.

Background Reactive oxygen species (ROS) have been implicated in the pathogenesis of many degenerative diseases. Antioxidant compounds can potentially be derived from plant sources. Consequently, investigations are been focused on plants as potential sources of treatments for oxidants-induced diseases. Some class of compounds that have been reported in many medicinal plants includes phenolics, alkaloids, saponins, tannins and terpenoids. Amaranthus belong to a more complex Amaranthaceae family and are widely used as leaf vegetables around the world. Interest has grown towards the search of Amaranthus species as potential sources of antioxidants. Hypothesis Compounds that can break the chain reaction initiated by reactive oxygen species are vital in treating and preventing disease caused by ROS. Method In this review, we did a comprehensive literature search on research articles published on the antioxidant activity of some Amaranthus species and in-vitro antioxidant assays. Results To establish the antioxidant potential of a plant, researchers customarily used more than a single evaluation method. Remarkable success has however been made using different evaluation methods in establishing the radical scavenging and antioxidant activities of some Amaranthus species. Some of the conventional methods enumerated in this write-up assessed the antioxidant activity by monitoring the radical scavenging activity of the plant extracts. Conclusions The antioxidant activity of the Amaranthus family has been reported to contribute largely to the various medicinal values. This review further outlined the antioxidant properties of Amaranthus species vis-a-vis their health benefits.

Background: Several local ablative modalities have been introduced for the treatment of locally advanced pancreatic cancer (LAPC). However, there is no consensus on how to evaluate the imaging response after treatment. A systematic review was performed regarding the use of imaging for response assessment in LAPC. Methods: A systematic literature search was conducted in PubMed. Studies reporting imaging outcomes were included in the review. Studies were excluded if the imaging outcomes could not be differentiated between different disease stages, tumor histology or surgical approaches. Results: Thirty-four studies were included in the analysis. Fourteen studies used standardized response criteria, while six studies did not report the response evaluation method. The rest used self-determined criteria, absolute size comparisons or similar methods. One study found a correlation between early systemic progression (