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Nitrosative stress, as an important oxygen metabolism disorder, has been shown to be closely associated with cardiovascular diseases, such as myocardial ischemia/reperfusion injury, aortic aneurysm, heart failure, hypertension, and atherosclerosis. Nitrosative stress refers to the joint biochemical reactions of nitric oxide (NO) and superoxide (O2–) when an oxygen metabolism disorder occurs in the body. The peroxynitrite anion (ONOO–) produced during this process can nitrate several biomolecules, such as proteins, lipids, and DNA, to generate 3-nitrotyrosine (3-NT), which further induces cell death. Among these, protein tyrosine nitration and polyunsaturated fatty acid nitration are the most studied types to date. Accordingly, an in-depth study of the relationship between nitrosative stress and cell death has important practical significance for revealing the pathogenesis and strategies for prevention and treatment of various diseases, particularly cardiovascular diseases. Here, we review the latest research progress on the mechanisms of nitrosative stress-mediated cell death, primarily involving several regulated cell death processes, including apoptosis, autophagy, ferroptosis, pyroptosis, NETosis, and parthanatos, highlighting nitrosative stress as a unique mechanism in cardiovascular diseases.

Papillary thyroid microcarcinoma (PTMC) has the highest incidence among all thyroid carcinomas. Although surgery is the primary treatment for PTMC, it inevitably leads to trauma and some complications. To formulate an optimal treatment strategy, we aim to clarify the risk factors for lymph node metastasis (LNM) in PTMC patients. This study retrospectively analyzed patients who underwent thyroidectomy during 1995-2015, and grouped them according to lymph node metastasis. Age, gender, tumor size, thyroid functions, Hashimoto's thyroiditis, multifocal tumor, extrathyroidal extensions, capsular invasion were analyzed. Of the 2434 PTMC subjects, proportion of patients with no LNM (NLNM), LNM, central LNM (CLNM), lateral LNM (LLNM), CLNM + LLNM were 82.9%, 17.1%, 7.0%, 7.6% and 2.5%. Patients with NLNM were older and had a lower proportion of males compared to patients with CLNM, LLNM and CLNM + LLNM (p 0.05). The NLNM group also had a smaller size of ultrasound tumor, lower proportion of multifocal tumor and extrathyroidal extension compared to CLNM, LLNM and CLNM + LLNM groups (p 0.05). On univariate analyses, male gender, age45 years, tumor size of pathology (˃0.75 cm), multifocality, and extrathyroidal extension were significantly associated with LNM. Multivariate analyses revealed that male gender, age45 years, multifocality were risk factors for LNM. In conclusion, PTMC patients with male gender, age45 years and multifocality should be evaluated carefully for possible LNM.

A monolithic active pixel sensor based direct detector that is optimized for the primary beam energies in scanning electron microscopes is implemented for electron back-scattered diffraction (EBSD) applications. The high detection efficiency of the detector and its large array of pixels allow sensitive and accurate detection of Kikuchi bands arising from primary electron beam excitation energies of 4 keV to 28 keV, with the optimal contrast occurring in the range of 8–16 keV. The diffraction pattern acquisition speed is substantially improved via a sparse sampling mode, resulting from the acquisition of a reduced number of pixels on the detector. Standard inpainting algorithms are implemented to effectively estimate the information in the skipped regions in the acquired diffraction pattern. For EBSD mapping, an acquisition speed as high as 5988 scan points per second is demonstrated, with a tolerable fraction of indexed points and accuracy. The collective capabilities spanning from high angular resolution EBSD patterns to high speed pattern acquisition are achieved on the same detector, facilitating simultaneous detection modalities that enable a multitude of advanced EBSD applications, including lattice strain mapping, structural refinement, low-dose characterization, 3D-EBSD and dynamic in situ EBSD.

Previous studies have demonstrated that the transplantation of alginate-poly-ʟ-lysine-alginate (APA)-encapsulated rat Leydig cells (LCs) provides a promising approach for treating testosterone deficiency (TD). Nevertheless, LCs have a limited capacity to proliferate, limiting the efficacy of LC transplantation therapy. Here, we established an efficient differentiation system to obtain functional Leydig-like cells (LLCs) from human stem Leydig cells (hSLCs). Then we injected APA-encapsulated LLCs into the abdominal cavities of castrated mice without an immunosuppressor. The APA-encapsulated cells survived and partially restored testosterone production for 90 days in vivo. More importantly, the transplantation of encapsulated LLCs ameliorated the symptoms of TD, such as fat accumulation, muscle atrophy and adipocyte accumulation in bone marrow. Overall, these results suggest that the transplantation of encapsulated LLCs is a promising new method for testosterone supplementation with potential clinical applications in TD.

Background Thyroid nodules are very common. Ultrasound (US) and fine needle aspiration (FNA) are both integral in cancer screening. This study investigated the concordance between thyroid nodule sizes measured by US and gross pathologic examination and their relationship with malignancy. Methods A retrospective design was used to select consecutive patients with proven carcinoma of the thyroid. The number and maximum diameter of nodules, rates and types of malignancy, as well as predictors of malignancy were determined. Results The 10 944 patients examined had 15 283 thyroid nodules, 44.6% of which were malignant. Of the 4449 nodules sampled by FNA and the 8748 not sampled by FNA, 76.5% and 30.5% were malignant, respectively. The sensitivity, specificity, positive and negative predictive values (NPVs), and overall accuracy of FNA based on final pathology were 97.9%, 96.3%, 98.8%, 93.5%, and 97.5%, respectively. Nodule sizes determined by US were comparable with most nodules having either the same size range (n = 2959, 77.7%) or differing only by one size range (n = 770, 20.5%). Conclusions Thyroid nodule size is inversely related to malignancy risk, as larger nodules have lower malignancy rates. Nodule size estimated by US shows relatively good correlation with final pathologic size. However, thyroid nodules should undergo FNA regardless of size. If the FNA is not benign, nodule size should influence therapeutic decision making.

A realistic finite element model considering the ploughing effect of cutting edge fillet was developed in high speed machining. Taking the hardened tool steel AISI D2 as the object of research, the cutting force and chip morphology were reasonably analyzed and compared with the actual results of cutting experiments, which verified the correctness of the model. Then, based on the model, the formation process of single serrated tooth was analyzed, while the effects of cutting heat and temperature field, material hardness and cutting speed on chip formation were explored. The research results indicate that: (1) The ploughing-effect has a great impact on the feed force, and for hardened tool steel AISI D2, the stagnation angle of 30o is more appropriate. (2) Also, stress concentration appears and shear slipping occurs along the shear plane in the process of serrated chip formation. The strain rate on the shear slipping surface is much greater than other places and the temperature gradient perpendicular to the shear plane is relatively higher. (3) The cutting force becomes larger with increasing the hardness value of workpieces, which causes the chip to more likely to produce serrated chips. (4) The fluctuation of cutting force is more significant as the cutting speed increases, which puts forward higher requirements for the tool and machine tool.

Indoor occupancy measurement plays an indispensable role in occupant-based intelligent control of building systems for energy conservation. In this paper, a novel algorithm is proposed to detect occupancy by analyzing the office surveillance videos. The algorithm uses a cascade classifier to detect human head, consisting of pre-classifier, main classifier and clustering analyzer. The pre-classifier uses three frame difference algorithm to search motion windows and employs a HOG-SVM module to filter most non-head areas quickly. The main classifier employs a convolution neural network to classify head windows with high recall and precision. The clustering analyzer utilizes K-means clustering to fuse sequential frames and verify the head detection result to further improve the accuracy. The advantages of the three stages are enhanced by separately determined parameters and then united by the particular combination. The innovation yields an outstanding overall performance. The algorithm is tested on the dataset of 80-h surveillance videos in an office. The experimental results show that the accuracy (correctness for presence of head) of occupancy measurement reaches up to 95.3% and the computational cost for a measurement is just 721 ms. It is applicable to both off-line data mining of stored videos and on-line detection of occupancy by intelligent video surveillance.

The application of big data technology in the field of indoor environment can be expected to achieve creative control. A feasible application is the data fusion of temperature, humidity, CO2 concentration, illuminance, and video to achieve novel control for air-conditioners (AC), outdoor air handling units (OAHU), and luminaires. This paper proposed a predictive control method for indoor environment using occupant number detected by combining video data and CO2 concentration. The occupant numbers detected by video data and CO2 concentration are inter-calibrated to improve the detection accuracy. The predictive control based on occupant number can achieve faster response, more stable indoor environment and energy saving as well compared with traditional control of indoor environment without using the information of occupant number change. Simulation and experimental studies were conducted to verify the feasibility and effectiveness of the predictive control based on occupant number. Results show that with regard to the experimental conditions the predictive control can save OAHU energy consumption by 85.2% and total energy consumption of AC and OAHU by 39.4%. Through experiments and simulation, it is verified that the proposed occupancy-based predictive control is a promising technique to save energy consumed by heating, ventilation and air-conditioning (HVAC) system while ensuring thermal comfort and indoor air quality.

Currently the indoor thermal environment control is mainly conducted based on the set points given by room occupants or based on PMV, which might cause problems of unreasonable temperature setting and unsatisfied individual thermal preferences of room occupants. The indoor thermal environment control method based on thermal sensation expression can solve these problems. However, control based on thermal sensation expression might frequently interrupt room occupants’ concentrations on work because this method needs occupants to input their thermal sensations, when their comfortable temperature range changes with the differences of the metabolic rate, clothing level etc. In an attempt to solve this problems, a new indoor thermal environment control method is proposed, which is to collect occupants’ skin temperature measured by infrared imaging to estimate the occupants’ current thermal sensation and predict their future thermal sensations. This paper introduces the control method of the system based on thermal sensation prediction. The control method was verified by building the test-beds and conducting a series of experiments. Experiment results show that 98% of the evaluations are neutral/satisfied/very satisfied with this control system, which means the proposed indoor thermal environment control method based on thermal sensation prediction is feasible for actual application.

There is a disk residual problem for the deletion mechanism of the Hadoop file storage system. This paper proposes a "plug and play" deletion method to achieve the purpose of completely deleting data. After simulation and recovery experiments, this method can effectively destroy the original data. At the same time, this method can be applied to some Big data clusters which are based on Hadoop. It does not need to redeploy the cluster and can be directly deployed in the already running big data cluster.

Ciliated muconodular papillary tumor (CMPT) is a peripheral non-endobronchial lung nodule, consisting of ciliated columnar cells and goblet cells with basaloid cell proliferation. Only about 50 cases confirmed by surgery have been reported in English literature worldwide. We present two surgical cases of CMPT in this report. Two patients presented with abnormal computed tomography findings but no obvious symptoms. The first patient’s intraoperative frozen examination was unable to distinguish benignity from malignancy, and he received lobectomy. The other patient’s intraoperative frozen examination indicated adenocarcinoma, but she received wedge resection for her refusal to lobectomy. The two patients’ postoperative pathological analysis finally confirmed the diagnosis of CMPT. We believe that our cases may be essential for pathologists and surgeons to improve their understanding.

With the rapid popularization of mobile devices, mobile devices such as smart phones have become an indispensable tool in people's daily life. Mobile devices not only bring convenience to human beings, but also bring criminal activities based on mobile devices such as SMS fraud, dissemination of harmful information, virus software and so on. Therefore, digital forensics for mobile devices under IOS operating system is of great significance for combating crime, information security and other issues.This paper first expounds the background and significance of mobile terminal forensics. This paper presents a digital acquisition method based on usbmuxd and iTunes for IOS devices. The method of parsing and storing raw data and restoring file directory are also provided.

ObjectivesThis study aims to summarise the features and trends of thyroid carcinoma in the past two decades in China.Design, setting and participantsClinical data obtained from 10 798 patients treated by thyroidectomy from 1994 to 2015 at the Department of General Surgery of the People’s Liberation Army General Hospital, Beijing, China were retrospectively analysed.Outcome measuresIncidence and histopathological features of thyroid cancer were compared and the risk factors for local lymph node metastasis analysed.ResultsOur data indicated a significant increase in the detection of thyroid cancer (from 16.8% to 69.8%, p<0.01). Among the 5235 thyroid cancer cases, papillary thyroid carcinoma (PTC) was the most common histotype, accounting for 95.1% of all malignancies over the 22-year period. Among the 4979 PTCs, micro-PTCs (mPTC) with the largest diameter ≤10 mm has gradually become the dominant form, and its percentage in PTCs has increased from 13.3% in the biennial period of 1994–1995 to 51.2% in 2010–2011. Furthermore, the size of the tumour has decreased significantly from 2.3±1.1 cm in 1994 to 1.2±0.9 cm in the largest diameter (p1 cm and male gender were the main risk factors for local lymph node metastasis (LNM), whereas patients over 45 years had lower risk.ConclusionsDuring the 22-year period, an increased detection of thyroid cancer, particularly mPTC, was found while the occurrence of LNM decreased. Our results suggest that the current preoperative diagnosis and risk stratification are adequate, supporting the published guidelines for the diagnosis of thyroid cancer.

Time-varying meshing stiffness (TVMS) of gears will decrease when gear fault occurs. Therefore, it can be used as an indication to reflect whether the gear is healthy. A pitting model where the pitting shape is considered as approximately a part of sphere is proposed herein. Then, the evolution model of a single pit is proposed. Formulas for computing the meshing stiffness of external spur gears with the proposed pitting model are deduced. Furthermore, pitting distribution models with four different pitting degrees are established, from perfect to severe pitting. The effect of different pitting degrees on TVMS are detailedly investigate experimentally. Compared with the finite element model, the proposed pitting model and computation method of TVMS is effective.

Building intelligent system has become one of the standard configurations in a public building even in a residential building. Intelligent buildings are expected to provide high-efficient, convenient, comfortable and energy-saving built environment so as to bring additional benefits. However, problems like sensor faults and control strategy flaws may result in low performance and high energy consumptions and maintenance costs are needed as well. Thus it is needed to synthetically evaluate the costs and benefits of intelligent systems to help building investors to make decisions. This paper proposes a cost-benefit evaluation method for building intelligent systems. Life cycle net present value (NPV) of all the costs and benefits, including tangible and intangible, is used as an index to evaluate the performance of the building intelligent systems. The proposed method puts emphases on the quantitative evaluation of intangible benefits using Analytical Hierarchy Process (AHP) method to determine the weights of each aspects of intangible benefit. The building energy consumptions are taken as an another emphasis as well. The proposed method is applied to evaluate three actual buildings to check its feasibility and effectiveness. Sensitivity analysis of NPV to energy consumption of the case study buildings shows that the energy consumption increase or decrease caused by different performances of intelligent systems can influence the positive or negative of NPV, which implies the building intelligent systems are worth of investment or not.

Various lighting and blind control methods have been presented to improve user comfort and reduce energy consumption simultaneously. However, there are opportunities to improve control performances by introducing more recent information and machine learning technologies which allow more comprehensive consideration of the balance between user comfort and system energy consumption. To be more specific, in terms of user comfort, unified set-point may not be desirable since different people may have different comfort preferences. In terms of energy consumption, the excessive cooling load of HVAC system should be considered in summer when utilizing solar incidence to reduce the lighting electricity consumption. The setting of the blind slat angle still has great room to improve instead of the cut-off angle. Moreover, users’ demands are not fully met, so sometimes they still want to override the automated control. Thus, a closed-loop satisfaction based system is developed in this paper, specifically we introduce an improved reinforcement learning controller to obtain an optimal control strategy of blinds and lights. It could provide a personalized service via introducing subjects perceptions of surroundings gathered by a novel interface as the feedback signal. The proposed system was implemented on a practical test-bed in an energy-efficient building. Compared with the traditional control, it can provide a more acceptable and energy-efficient luminous environment.

Based on the perspective of the value chain of agricultural science and technology innovation, in this paper, we divided the process of agricultural science and technology innovation into two stages: the Research and Development (R&amp, D) of agricultural technology and the application of agricultural technology. We took the efficiency of agricultural science and technology innovation of the two stages as a comprehensive index measure for the development of agricultural science and technology innovation in China. On this basis, we used social network analysis to establish a two-stage spatial correlation network for the innovation development of agricultural science and technology in China. The spatial-temporal evolution trends, structural characteristics, and influencing factors of the network were analyzed from the three aspects of the overall, local, and individual network structure. The results show that: a. The development of agricultural science and technology innovation in China demonstrated a clear spatial correlation and spillover effect, and the spatial correlation network was in a connected state. b. The network had the distribution characteristics of &lsquo, core-edge&rsquo, and strong stability, and the hierarchical structure of the members of each province in the network was gradually broken. c. The differences at the market level in agricultural science and technology, the differences in government support for agriculture, the geographically adjacent relationships, and the level of agricultural economic development were important factors affecting the spatial correlation of agricultural science and technology innovation. This study provides a policy reference to use a cross-regional coordinated development mechanism to solve the uneven and asymmetry problem of the distribution of elements in various regions in China.

Gears are prone to failures, which are difficult to detect in the early stage. In this study, the time-varying mesh stiffness of gears teeth with different crack lengths is calculated, and the effects of spalling with different widths, lengths, and locations on the time-varying mesh stiffness of gears are investigated. Considering the time-varying mesh stiffness and sliding friction between teeth, a dynamic gear model with six degrees of freedom is established. Then, the dynamic displacement response of the gear system in the vertical direction is solved by simulation. Due to the difficulty of extracting early fault features, a method of stiffness segmentation is proposed. A short-time Fourier transform is applied to each signal corresponding to the stiffness segment. Changes in the dynamic responses in the time domain, frequency domain, and time–frequency domain with the extension of gear fault are examined. Finally, the trends of various statistical indicators in the time domain and frequency domain with respect to the level of fault extension are compared and analyzed. The results show that the impulse factor is sensitive to fault characteristics.

We aimed to investigate the association between excess body mass index (BMI) and papillary thyroid cancer (PTC) in an operative population, and the impact of higher BMI on clinicopathological aggressiveness of PTC.Charts of 10,844 consecutive patients with thyroid nodules undergoing partial or total thyroidectomy between 1993 and 2015 were reviewed. Patients diagnosed with PTC were stratified in 4 groups: BMI < 18.5 (underweight), 18.5 ≤ BMI < 24 (normal-weight), 24 ≤ BMI < 28 (overweight) and BMI ≥ 28(obese). The impacts of high BMI on prevalence and clinicopathological parameters of PTC were retrospectively analyzed in both univariate and multivariate binary logistic regression analysis.For every 5-unit increase in body mass, the odds of risk-adjusted malignance increased by 36.6%. The individuals who were obese and overweight were associated with high risk of thyroid cancer [odds ratio (OR)= 1.982, P < .001; OR= 1.377, P < .001; respectively] compared to normal weight patients, and this positive association was found in both genders. Obesity was independent predictors for tumors larger than 1 cm (OR = 1.562, P < .001) and multifocality (OR = 1.616, P < .001). However, there was no difference in cervical lymph node (LN) metastasis among BMI groups. Crude analysis showed BMI was associated with advanced tumor-node-metastasis (TNM) stage (relative risk, approximately 1.23 per 5 BMI units, P < .001), but this association disappeared after adjusting for confounding factors.Obesity was significantly associated with the risk of PTC in a large, operative population. Higher BMI was significantly associated with larger tumor size and multifocal tumor.

The study aimed to investigate the gender-related differences of disease onset, age distribution, blood type, clinical characteristics, and malignant behaviors of differentiated thyroid carcinoma (DTC) in Chinese patients. A total of 7385 consecutive thyroid cancer patients who underwent thyroidectomy were retrospectively reviewed. 4087 (55.3%) were diagnosed as benign and the other (3298, 44.7%) were as malignant. DTC accounted for 97.6% in the malignant tumor. More single nodules turned out to be DTC in male compared to multiple nodules (46.9% vs. 40.4%, P = 0.004). The proportion increased along with the increase of year during 2000–2013, which was from 7.5% to 68.1% in males and from 16.2% to 66.7% in females. The level of preoperative TSH was significantly higher in patients with DTC compared to the patients with benign (1.97 vs. 1.57 mIU/L, P

The chiller system in a building accounts for the main part of the building's total energy consumption, so it is critical to optimize the operation of chiller system for the purpose of saving energy. A chiller system generally consists of evaporation side and condensing side. The condensing side includes chillers, cooling water pumps and cooling towers, which form a subsystem of cooling water. It is a typical optimization problem to minimize the total energy consumption of cooling water subsystem. This paper discusses how to solve the optimization problem of the cooling water subsystem and proposes a simple optimal control rule for field operation based on the optimization results.

In this paper, Simulink model is built to simulate the chilled water system of a real building. The optimal chilled water flow rate and chilled water supply temperature are found out by traversing the constrained parameter values under different working conditions. The simple optimal control rules are developed based on the optimal solutions. Optimal control rules can reduce the total energy consumption of the chillers, chilled water pumps, and air handling units by 17.55% compared with tradition control.

With the rapid development of green building, it is important to check the energy and environmental performance of the green building post occupation. This paper focuses on how to evaluate the energy performance of a green building's cooling/heating source of the air-conditioning system post occupation. The operation of the cooling/heating system is checked to find out the problems and optimal control strategy is proposed. The performance of proposed control strategy is verified by simulation and experiments. Simulation analysis confirms that the proposed control strategy can save 21.3% of the heating energy under the condition of satisfying the indoor temperature requirement. Experiments carried out in the building show that the experiment day's heating energy was saved by 19.5% compared to the comparison day, and the total electricity consumption of the cooling/heating source system was saved by 27.4%.

In this research, a normal building and low energy consumption building were chosen to compare and analyze heating and cooling load characteristics. Firstly, the abstract of two buildings were carried out. Secondly, methodology of measurement and calculation was researched. At last the heating and cooling load of two buildings was examined using this methodology.

This paper proposes a novel fan coil unit (FCU) control logic, which controls fan speed level and water valve duty ratio to make both temperature and humidity match the set-points. The performance of the proposed control logic is compared with two other control logics using simulation. One of them is to open/close water valve to make room air temperature match the set-point, which is the usually used control logic. Another control logic is to open/close water valve according to a duty ratio decided by a fuzzy logic. The simulation results show that the proposed control logic can achieve control performance: the temperature is tset ± 0.5°C and humidity is dset ± 3% when duty ratio period is 300 s, and the temperature is tset ± 1°C and humidity is dset ± 7% when duty ratio period is 600 s. The control performance of proposed control logic is better than the valve on/off control logic and the fuzzy control logic.

This paper proposes a data-driven learning method to describe the personal thermal complaint behavior in a complaint-driven environment control system. The complaint-driven system only uses personal human complaints to control the personal office environment. It avoids the user's direct control on the set-point of the room, which usually results in unreasonable and uncomfortable set-point. A two-stage classifier model is proposed, using personal thermal compliant data with respect to the transient and steady complaint behaviors. The classifier structure is developed based on the properties of human thermal perception with parameters to learn for different users. Quantitative results using experimental data show that the model has lower false negative rate than traditional data-driven classification model and acceptable false detection rate. Practical implementation and subjects' questionnaire evaluation demonstrate the satisfying performance of the model in real environment control. We also discuss the limitations and potential extensions of the model at the end of this paper.

Recent advances of information technology and the low cost of computing devices make it possible to collect end users' true thermal sensations at the building operation stage. This enables us to build personalized thermal comfort model from a new aspect. This paper proposes a data-driven method to describe the personalized thermal comfort in ordinary office environment. The model structure shows the condition of heat balance of human body, with four personalized coefficients estimated by on-line voting data. The adjustable coefficients provide the freedom to capture the personal differences in thermal comfort requirement. In contrast, the well-known PMV model is only an average model, which cannot reflect such differences. The model performance is evaluated by a field experiment study. A personal energy saving potential analysis is also presented as one of the applications. Both the experiment results and simulation results demonstrate the high accuracy of the data-driven model and the feasibility of the application in investigating personal energy saving potentials.

For the purpose of achieving high performance of intelligent buildings, it needs to pay expanses for maintaining the intelligent systems. So it is in great need to analyze the costs and benefits of building intelligent system to help building owners to make decision on installing intelligent systems or not. This paper proposes an investment-benefit assessing approach for building intelligent systems. Net Present Value (NPV) is used as an index to evaluate the performance of building intelligent system. The NPV is calculated by analyzing the initial capital investment, maintenance costs, and the tangible and intangible benefits in building life cycle. The intangible benefits are quantified using a series of indexes which represent the cash flows brought by the intangible benefits. Different weights of these indexes are used to express the different contributions of these intangible benefits. Analytical Hierarchy Process (AHP) method [ is used to quantify the weights of the indexes.

The proportion of electricity used for civil buildings is increasing, which intensifies the imbalance between the demand side and supply side of the grids and leads to a large decrement in grid efficiency and large energy losses. The phase change material (PCM) can be used to store numerous heat or cold for heating, ventilation, and air-conditioning (HVAC) systems for its phase change temperature range suitable for maintaining comfortable building thermal environment. Utilizing PCM for HVAC is an important way to mitigate fluctuations in the power consumption of buildings. This paper proposes a new type of air-conditioning duct combined with PCM. The demand shift effects of the PCM integrated air-conditioning duct is studied through experiments. The PCM material ingredients are designed according to the required phase change temperature range. The feasibility of PCM application in HVAC ducts is verified. The results show that air-conditioning duct combined with PCM can keep the indoor temperature in a comfortable range during the power peak load after shutting down chiller.

Buildings account for nearly 40% of global energy consumption. About 40% and 15% of that are consumed, respectively, by HVAC and lighting. These energy uses can be reduced by integrated control of active and passive sources of heating, cooling, lighting, shading and ventilation. However, rigorous studies of such control strategies are lacking since computationally tractable models are not available. In this paper, a novel formulation capturing key interactions of the above building functions is established to minimize the total daily energy cost. To obtain effective integrated strategies in a timely manner, a methodology that combines stochastic dynamic programming (DP) and the rollout technique is developed within the price-based coordination framework. For easy implementation, DP-derived heuristic rules are developed to coordinate shading blinds and natural ventilation, with simplified optimization strategies for HVAC and lighting systems. Numerical simulation results show that these strategies are scalable, and can effectively reduce energy costs and improve human comfort.

Building Automation Systems (BASs) have been developed to provide a safe, comfortable, and energy-efficient indoor environment for households. A tremendous volume and enormous variety of building data are collected and stored in BASs. However, these data could not be completely utilized by traditional data analytics due to the huge volume and heterogeneous nature. In this paper, case studies are carried out using data mining techniques to find the potential value and discover the hidden knowledge in building area. We proposed a new fault diagnosis approach for chillers/AHU during operation. A promising guide to knowledge selection and interpretation in associate rule mining is presented to capture more energy saving potential opportunities. We also demonstrate the importance of occupancy information in improving building operation performance. The approaches and findings presented are not only for these cases but also feasible for more applications.

Pituitary adenomas, central neurocytomas, and pineal tumors are the major primary neuroendocrine neoplasms of the central nervous system; they are affecting mainly young adult and adult patient populations. Accumulation of research and clinical data clarify slowly those tumors’ morphology and biological behavior as we understand the molecular alterations of the tumors. This chapter is trying to review the recent development in this field, which may help us to make more accurate diagnoses and direct the clinicians to choose more appropriate treatment options for our patients.

Meningeal melanocytoma is an uncommon pigmented neoplasm that affects the CNS and develops in the cranial and spinal leptomeninges. Here we report on a case of malignant transformation of intracranial supratentorial meningeal melanocytoma which recurred after 3 years as malignant melanoma. This case demonstrates that the biological behavior of melanocytoma is uncertain and that these lesions may recur as malignant melanoma.

A methodology for optimizing the operation of heating/cooling plants with multi-heat-source equipments is proposed. The methodology decides the optimal combination of the running machines to minimize the energy consumption of a heating/cooling plant. The energy consumption, energy cost and carbon dioxide emission are simulated using a tool developed in the MATLAB ® Simulink ® environment, embedded with a module developed using MATLAB ® Stateflow ® that can automatically decide the on/off states of heat source machines corresponding to cooling and heating loads and an operational priority order of heat source machines. A case study is introduced to demonstrate the methodology, which is an actual heating/cooling plant located in Osaka, Japan. The plant consists of two absorption chiller/heaters, one centrifugal chiller, one ice chiller, and two air-source heat pumps. The proposed methodology is used to simulate the plant performance at six different operational priority orders of heat source machines. The best operational combination can reduce primary energy consumption by 19.7%, energy cost by 12.8%, and carbon dioxide emission by 29.6%, compared to present operation.

The set point of the Heating, Ventilating and Air Conditioning (HVAC) system is usually given by the Predicted Mean Vote (PMV) model. However, the individual differences in thermal preference often incur dissatisfactions in a group, which indicates that the PMV model may have bias in predicting the thermal comfort for a group of occupants. It has great potential to find a more suitable model to determine room set points. In this paper, a satisfaction based group comfort model is developed based on our previous work. We build an individual comfort model for each person according to their satisfaction and take the convex hull of these comfort zones. Some experiments are implemented for the group under both cooling and heating conditions in an ordinary office environment. The experimental results including indoor environment control, users' acceptance, working efficiency and energy consumption are supporting the presented group model.

The diagnosis of malignant thyroid nodules is still a clinical challenge. This study aimed to determine the ultrasonographic characteristics of papillary thyroid carcinoma. The ultrasonographic and pathological data of 2453 thyroid nodules in a cohort of 1895 Chinese patients who underwent thyroidectomy from January 2010 to December 2012 were retrospectively reviewed. Anteroposterior and transversal (AP/TR) diameters ≥1, solid structure, infiltrative margins, hypoechoic appearance, and microcalcifications were more common in malignant nodules than in benign nodules (P 10 mm). However, in small nodules (diameter ≤10 mm), only AP/TR ≥1 and infiltrative margins were independent risk factors of malignancy (P

Based on the theories of digital conjugate surface and gear meshing, a generating method for digital gear tooth surfaces (DGTS) is demonstrated in this paper. The research focuses on the conjugate motion between the DGTS, represented by discrete points, and the cutter figuration determined by analytic function in the manufacture process. Conjugate points in the cutter section corresponding to the discrete points on the digital surface and conjugate movements are solved. Automated sequence arrangements of the generating movement parameters have been performed and the discrete generating movements are interpolated in a continuous conjugate motion along the order. Strategies of error analysis and error compensation are also discussed in this paper. Computer-simulated examples of the generating machining of involute DGTS and non-standard shaped DGTS, the parameters of machining motions and real tooth surfaces verify the developed method. The research develops a new idea for the machining of DGTS, which breaks the limitations of conventional approaches based on analytic surfaces. It is of important theoretical and practical value to manufacture digital surfaces. Our method is not only be applicable in generating machining of discrete DGTS and analytic gear tooth surfaces with complex geometric design, but also in contributing to the processing of discrete digital cam and other 3-D digital surfaces .

This paper proposes a model that can estimate filter resistance using estimated air-conditioner indoor unit air flow rate, which is tightly related to filter fouling conditions. Two sorts of value are used as inputs to estimate air flow rate. One is the power consumed by the fan in the indoor unit of a room air-conditioner and the other is the thermal performance of a room air-conditioner. For the room air-conditioners that the real-time indoor unit fan power consumption is available, fan power consumptions are used as inputs to estimate filter resistance. For the room air-conditioners that are equipped with refrigerant pressure and temperature sensors, this model estimates filter resistance using refrigerant pressure and temperature, air temperature or enthalpy difference between supply and indoor air. This model was validated using a really running multi-evaporator Gas-engine Heat Pump (GHP) system. The maximum and average difference between estimated and measured filter resistance are 12.72% and 5.89% when using the fan power consumption as inputs. When using the air-conditioner thermal performance data, the maximum and average estimation errors are 13.12% and 5.96%. The validation results show that this model is accurate enough for estimating filter resistance. Based on this model, the method for commissioning filters in air-conditioner is discussed. This method is useful for automatically estimating filter resistance and reminding users timely to clean or replace a filter to prevent wasting energy and to maintain desirable indoor environment.

In the summer of 2002, measurements were simultaneously performed to investigate the characteristics of heat flow in urban areas at three locations in Kyoto city: (1) a commercial urban area mixed with low-rise traditional residential buildings that represents the urban area of Kyoto; (2) a university campus area with lots of green zones; and (3) a plaza covered with a concrete slab which was used as a reference point of measurement. Heat flux of boundary layer over the three locations and the surface temperatures of building walls and streets were measured to investigate the urban thermal environment. For the analysis, a new simulation code was developed by combining unsteady state heat conduction of building walls and grounds, radiation heat exchange between them, and airflow by computational fluid dynamics (CFD). By using this code, the thermal environment of the urban areas such as air temperature, humidity, wind velocity, and boundary layer heat flux was predicted and compared with the measured results. It was found that this model could predict the real thermal environment of the urban area. Using this code, the effect of additional green on roofs and grounds can be investigated in order to mitigate urban heat island and to improve urban thermal environment at the street level.

In order to detect the reliability of the high-low voltage comprehensive protector, the paper designs a set of comprehensive protector universal test system. EDA measurement and control modules measure the related parameters of the comprehensive protector. PC analyses and processes these parameters, and then determines the reliability of the comprehensive protector. Automatic level of the system is high. The test results are accurate. Reliability of the software system is high, and the system is easy to be developed.

Heating, Ventilating and Air Conditioning (HVAC) systems are used to provide adequate thermal comfort to occupants of spaces within buildings. The well-recognized PMV model which represents the ‘predicted mean vote’ (on the thermal sensation scale) of a large population of people exposed to a certain environment is often used by design engineers to determine the size and capacity of HVAC system. In terms of operation, however, due to the differences in personal thermal comfort preferences, it might not be good to determine the room set points based on the general PMV model. In this paper, we extend our previous efforts in modeling the single occupant thermal comfort zone to determining the group occupant thermal comfort zone in an ordinary office environment. Experimental results show that thermal comfort zone for a group of occupants is different from the PMV model.

The performance curves of typical chillers available from the present market are investigated. These performance curves are fitted to develop a chiller model, which together with pump and cooling tower models are used to study the optimal control strategy for condensing side of chiller systems. The optimization objective is to minimize the total energy use of chillers, condensing pumps, and cooling tower fans. The optimization problem is solved by traversing all possible combinations of chiller water flow rates, cooling tower air flow rates, and ambient air wet-bulb temperatures. Then the optimal solutions are analyzed to find out applicable rule-based control strategies that are not far from optimal solutions and reliable as well. The rule-based control strategy is to keep one or two constant cooling water flow rates during whole operational season according to the number of running chillers and to keep cooling tower air flow rate at a constant ratio to cooling water flow rate. Because this rule-based control strategy does not use sensor measured data, such as wet-bulb air temperature, it is free of sensor faults and can be more robust and reliable than the currently used control strategies, most of which use cooling water temperature or ambient air wet-bulb temperature to decide the cooling water flow rate or air flow rate of cooling tower fans.

Intelligent building system attracts more and more attention in both academic and industrial communities. Learning human comfort requirements and incorporating it into building control system is one of the important issues. In the traditional HVAC control system, the thermal comfort and the acoustic comfort are often conflicted and we lack of a scheme to trade off them well. In this paper, we propose a unified control framework based on reinforcement learning to balance the multiple dimension comforts, including the thermal and acoustic comforts. We utilize the user's complaints in thermal and acoustic sensations as feedback and combine the current environment and devices information to learn the personalized optimal control policy using online Q-learning. The challenge caused by the complaints is coped with an incorporated perception estimation scheme in the Q-learning reward design. Both simulation results and the field experimental results demonstrate the effectiveness of the algorithm, especially in the adaptivity to the individual tradeoff between thermal and acoustic comfort.

The drastic growth in the consumption of electrical household appliances becomes a concerned issue in recent years. It is difficult for traditional methods to consider both subject's comfort and energy savings. Moreover, different people have different comfort preferences and requirements. In this paper, a novel integrated control method of blind and lights is proposed and it can provide an intelligent and comfortable living environment in an office building. The presented method has the ability to intelligently learn the subjects' comfort preferences by analyzing their behaviors. Besides, an energy oriented control is proposed by considering the sun position and solar radiation into the room. Our method is implemented on a practical test bed in an energy-efficient building in the campus. The subject experiments are conducted to test the method and platform. After a couple days' learning, the platform can capture the subjects' preferences on the blind and lights. Compared to the traditional method, our method provides a more comfortable and energy-efficient illuminance environment in office building.

Learning the model of user's thermal complaints in the daily office environment and apply it to the control of Heating, Ventilating, and Air Conditioning (HVAC) is more user-friendly and intelligent. But the modeling of complaint behavior is challenging because of the stochastic complaint time, unbalanced sample sets, individual differences and uncertainties. Most existing human comfort models are not feasible under those conditions. In this paper, we propose a novel one-class (complaint only) classifier to model individual human complaints. The method extracts the pare-to-frontier set of the samples of each individual and uses a multi-linear classifier to describe the boundary of the complaint region in parameter space. Virtual no-complaint samples are synthesized to calculate the classifiers' false positive rate. Real experimental results show that the method have lower false negative rate than traditional classifiers, which have more significant value in avoiding complaints. We also propose a method to do trade-off between false negative rate and false positive rate.

Environment and energy issues are considered to be most urgent things nowadays even in future. A lot of researches have been conducted to study how to prevent global warming and reduce energy consumption. In the field of building and urban environment, green roof attracts a lot of researchers’ attention because it is considered to be a good solution for improving urban thermal environment by mitigating heat island and to reduce building cooling energy consumption by reducing cooling load. Alexandria et al. (2008) analyzed how much the urban canyon temperature can be decreased due to green walls and green roofs. Takebayashi et al. (2007) compared the building surface heat transfer of green roofs with common roofs and high reflection roofs. Kumar et al. (2005) developed a mathematical model to evaluate the cooling potential and solar shading effect of green roofs. Wong et al. (2003) analyzed the thermal benefits of green roofs in tropical area. Di et al. (1999) measured an actual green wall to analyze how much cooling effect is achieved. Elena (1998) analyzed the cooling potential of green roofs. Besides studying the green roofs’ benefits of heat island mitigation and thermal isolation, the cost vs. benefit is also analyzed (Clerk et al., 2008) and green roof plants selection is analyzed as well (Spala et al., 2008).