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The study presents a life cycle assessment (LCA) of a next-generation lithium ion battery pack using silicon nanotube anode (SiNT), nickel–cobalt-manganese oxide cathode, and lithium hexafluorophosphate electrolyte. The battery pack is characterized with 63 kWh capacity to power a midsized electric vehicle (EV) for a 320 km range. A novel LCA model is developed through the inventory analyses of the SiNT anode manufacturing conducted on the basis of our lab-scale experimentation, and the inventory of the NMC-SiNT battery manufacturing is constructed from our industrial partners’ pilot-scale battery production facilities. The upstream and downstream inventory analyses are performed through professional LCA databases and public literature. The obtained impact results of the NMC-SiNT battery are benchmarked with those of a conventional NMC-Graphite battery pack under the same driving distance per charge baseline. The results show that the NMC-SiNT battery has comparable environmental impacts with the conventi...

Background Osteoporosis and cardiovascular disease (CVD) are age-related diseases. It is reported that patients with CVD have a higher risk of bone loss. This retrospective study sought to reveal the association between osteoporosis and CVD in Chinese women. Although epidemiological evidence has indicated a relationship between the two, clinical data in southeast China are lacking. Methods In total, 2873 participants completed the baseline survey from January 2007 to October 2019, and 2039 were included in this retrospective study. We divided all subjects into an osteoporosis group and a non-osteoporosis group based on their bone mineral density (BMD). Dual-energy X-ray absorptiometry (DXA) was used to examine BMD. The general information came from the questionnaire survey. Cardiovascular diseases were defined by asking participants at the first visit and checking relevant medical records if they had suffered from hypertension, coronary heart disease, or cerebral infarction. Results According to the criterion, the osteoporosis group had 678 subjects, and the non-osteoporosis group had 1361 subjects. Subjects in the osteoporosis group had a significantly higher prevalence of hypertension and coronary heart disease. Besides, the proportion of subjects who drank tea and drank milk were relatively higher in the osteoporosis group. The odds ratio (OR) for suffering from osteoporosis was high if the patients had hypertension. Conclusions This study indicated that Chinese postmenopausal women with osteoporosis had a higher prevalence of hypertension. Hypertension was significantly associated with osteoporosis.

Background: Osteoporosis and cardiovascular disease (CVD) are age-related diseases. According to some studies, patients with CVD have a higher risk of bone loss. This retrospective study intended to reveal the correlation between osteoporosis and CVD in Chinese women. Although epidemiological evidence has provided evidence of the relationship between the two, it lacks clinical data in southeast China.Methods: The 2873 participants completed the baseline survey from January 2007 to October 2019, and 2496 were included in this retrospective study. We divided all subjects into the osteoporosis group and the non-osteoporosis group based on their bone mineral density. Dual-energy x-ray absorptiometry (DXA) was used to examine bone mineral density. The general information came from the questionnaire survey and medical records. Results: According to the criterion, the osteoporosis group had 799 subjects, with a mean age of 64.19 years. The non-osteoporosis group had 1697 subjects, with a mean age of 61.03 years. Subjects in the osteoporosis group had a significantly higher prevalence of hypertension and coronary heart disease. Besides, there was a higher probability of drinking tea and drinking milk in the osteoporosis group. In correlation analysis, the occurrence of osteoporosis correlated positively with hypertension and coronary heart disease. Logistic regression analysis showed that the odds of osteoporosis was high if participants had hypertension, coronary heart disease, or drank tea and drank milk. Conclusions: This study indicated that patients with osteoporosis had a higher prevalence of CVD in Chinese women, and CVD is one of the hazard factors for osteoporosis.

Recommendation systems are widely used to help their netizens find what they want from cyber space and many various applications have been developed in different areas like news feeding, entree recommending and online shopping, etc. Many researches have found that their system performance is obsession with diversity-accuracy dilemma, and recommender has to balance recommendation sequence results. CBR-recommender is suggested for it has a comprehensive expression of human sense, logics and result explanation, and has more system flexibility to integrate many AI tools in dealing with such diversity-accuracy dilemma. Covering algorithm is also proposed to dynamically cluster similar users or items as subdomain for which all users are dynamitic divided into multiple clusters according to a certain criterion. Our experiments results indicate that users with similar hobbies are assigned to the same sub-domain as many specific sub-classes, and the refined classification results are more conducive for the problem-solving.

Background The purpose of this study is to investigate the optimal surgical options for different kinds of advanced hip tuberculosis, which are still controversial. Methods We reviewed seven advanced hip tuberculosis patients received operations from November 2014 to September 2018. All patients received anti-tubercular chemotherapy at least 2 weeks preoperatively and twelve months postoperatively. One active case with sinus tract of seven patients underwent three-stage operations including two debridements/cement spacer implantations and one total hip arthroplasty, while the other six cases received one = stage arthroplasty surgery. All patients are followed up based on Harris score, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR) and X-ray. Results The mean follow-up time was 41.6 months, while no reactivation was detected. The average Harris score increased from 40.0 preoperatively to 89.4 at the final follow-up. ESR of 3 active hip tubercular cases decreased from 143.7 mm/L at diagnosis time to 6.7 mm/L at the final follow-up. CRP of 3 active hip tubercular cases decreased from 80.01 mg/L (range, 37.34-136.92 mg/L) at diagnosis time to 1.91 mg/L (range, 1.05-2.57 mg/L) at the final follow-up. The ESR and CRP of all patients had returned to normal level at the final follow-up. No prosthesis dislocation, loosening and neurovascular injury was found. Conclusions THA is an effective and safe option for hip tuberculosis. The essentials for good outcome include early diagnosis, regular perioperative anti-tubercular chemotherapy, radical debridement of inflamed tissue and necrotic bone, staged-operation if necessary.

BackgroundRecent research has suggested that cardiotrophin-like cytokine factor 1 (CLCF1) may be an important regulator of bone homeostasis. Furthermore, a whole gene chip analysis suggested that the expression levels of CLCF1 in the peripheral blood mononuclear cells (PBMCs) were downregulated in postmenopausal women with osteoporosis. This study aimed to assess whether the expression levels of CLCF1 in PBMCs can reflect the severity of bone mass loss and the related fracture risk.MethodsIn all, 360 postmenopausal women, aged 50 to 80 years, were included in the study. A survey to evaluate the participants’ health status, measurement of bone mineral density (BMD), routine blood test, and CLCF1 expression level test were performed.ResultsBased on the participants’ bone health, 27 (7.5%), 165 (45.83%), and 168 (46.67%) participants were divided into the normal, osteopenia, and osteoporosis groups, respectively. CLCF1 protein levels in the normal and osteopenia groups were higher than those in the osteoporosis group. While theCLCF1mRNA level was positively associated with the BMD of total femur (r= 0.169,p= 0.011) and lumbar spine (r= 0.176,p= 0.001), the protein level was positively associated with the BMD of the lumbar spine (r= 0.261,pr= 0.236,p= 0.001), greater trochanter (r= 0.228,p= 0.001), and Ward’s triangle (r= 0.149,p= 0.036). Both the mRNA and protein levels were negatively associated with osteoporosis development (r= − 0.085,p= 0.011 andr= − 0.173,p= 0.014, respectively). The association between CLCF1 protein level and fracture risk was not significant after adjusting for BMD.ConclusionsTo our knowledge, this is the first clinical study to show that CLCF1 expression levels in the PBMCs of postmenopausal women can reflect the amount of bone mass or the severity of bone mass loss.

Lithium-sulfur (Li-S) battery is widely recognized as the most promising battery technology for future electric vehicles (EV). To understand the environmental sustainability performance of Li-S battery on future EVs, here a novel life cycle assessment (LCA) model is developed for comprehensive environmental impact assessment of a Li-S battery pack using a graphene sulfur composite cathode and a lithium metal anode protected by a lithium-ion conductive layer, for actual EV applications. The Li-S battery pack is configured with a 61.3 kWh capacity to power a mid-size EV for 320 km range. The life cycle inventory model is developed with a hybrid approach, based on our lab-scale synthesis of the graphene sulfur composite, our lab fabrication of Li-S battery cell, and our industrial partner's battery production processes. The impacts of the Li-S battery are assessed using the ReCiPe method and benchmarked with those of a conventional Nickle-Cobalt-Manganese (NCM ) -Graphite battery pack under the same driving distance per charge. The environmental impact assessment results illustrate that Li-S battery is more environmentally friendly than conventional NCM-Graphite battery, with 9%–90% lower impact. Finally, the improvement pathways for the Li-S battery to meet the USABC (U.S. Advanced Battery Consortium) targets are presented with the corresponding environmental impact changes.

Though Deep Learning CNN is mostly used in UAV power line-inspection system for the application of intelligent image recognition technology, can design image features easily and has strong adaptability to complex environments, but three problems deafly influence the actual results of application system such as insufficient image samples library, scarce labeling samples, and absent open-data source. To conquer these problems, CBR is proposed as a strategy for knowledge reasoning, which transform the similar case-space to a new situation for problem-solving, so the combination of RBR and CBR is expected to construct our flexible case- decision diagnosis system, which integrates efficient machine learning methods to give their full advantages to guarantee the good performance of the system for fault detection. The on spot experimental results indicates our system performs efficiently, assist people in decision-making and can find potential equipment faults.

Supplemental Digital Content is available in the text, Osteoporosis (OP) is a metabolic bone disease that can cause structural changes in bone marrow cavity. Bone marrow is the hematopoietic organ of adults. Accumulating evidence has shown a close connection between bone marrow hematopoietic function and bone formation. Some studies have revealed that OP is associated with hematopoiesis. However, the relationship is not definite. This study aimed to evaluate the association between peripheral blood cell counts (white blood cells [WBC], red blood cells [RBC], platelets [PLT]), hemoglobin [HGB], and bone mineral density [BMD]) in a sample of Chinese postmenopausal women. This is a retrospective study involving 673 postmenopausal women cases. The BMD of lumbar spine and left hip joint were measured by dual-energy X-ray absorptiometry. The levels of blood cell counts and HGB were measured and analyzed. The study results showed the WBC, RBC, PLT, and HGB levels of postmenopausal women in the OP group were all higher than those in the non-osteoporosis group. Spearman linear trend analysis and partial correlation analysis demonstrated that BMD was negatively correlated with WBC, RBC, PLT, and HGB in postmenopausal women. Due to the differences between different countries and races, and there are few studies on the association of BMD with peripheral blood cell counts and HGB in Chinese Postmenopausal Women. Therefore, more large sample studies are needed.

Temperature monitoring is important for improving the safety and performance of Lithium Ion Batteries (LIB). This paper presents the feasibility study to insert flexible polymer embedded thin film thermocouples (TFTCs) in a lithium ion battery pouch cell for in-situ temperature monitoring. A technique to fabricate polyimide embedded TFTC sensors on glass substrates and later transfer it onto thin copper foils is presented. The sensor transfer process can be easily integrated into the assembly process of a pouch cell, thus holding promise in implementing in Battery Management Systems (BMS). Internal temperature of the LIB pouch cell was measured in-situ when the sensor embedded battery was operated at high rate charge–discharge cycles. The polyimide embedded TFTCs survived the battery assembly process and the battery electrolyte environment. It is observed that the heat generation inside the battery is dominant during the high-rate of discharges. The developed technique can serve to improve the battery safety and performance when implemented in battery management systems and enhance the understanding of heat generation and its effects.

Although silicon nanowires (SiNW) have been widely studied as an ideal material for developing high-capacity lithium ion batteries (LIBs) for electric vehicles (EVs), little is known about the environmental impacts of such a new EV battery pack during its whole life cycle. This paper reports a life cycle assessment (LCA) of a high-capacity LIB pack using SiNW prepared via metal-assisted chemical etching as anode material. The LCA study is conducted based on the average U.S. driving and electricity supply conditions. Nanowastes and nanoparticle emissions from the SiNW synthesis are also characterized and reported. The LCA results show that over 50% of most characterized impacts are generated from the battery operations, while the battery anode with SiNW material contributes to around 15% of global warming potential and 10% of human toxicity potential. Overall the life cycle impacts of this new battery pack are moderately higher than those of conventional LIBs but could be actually comparable when considering the uncertainties and scale-up potential of the technology. These results are encouraging because they not only provide a solid base for sustainable development of next generation LIBs but also confirm that appropriate nanomanufacturing technologies could be used in sustainable product development.

Freestanding TiO2 nanotube array films are fabricated and first applied as electrodes in perovskite CH3NH3PbI3 sensitized solar cells. The device demonstrates improved light absorption with more than 90% of light absorbed in the whole visible range and a reduced charge recombination rate, leading to a significant improvement of the photocurrent and efficiency. This study suggests a promising way of improving the conversion efficiency of perovskite solar cells through novel electrodes.

Band gap opening and modulating are critical in dictating the functionalities of single walled carbon nanotubes (SWCNTs) in a broad array of nano-devices. Using first-principles density functional theory calculations, a class of semiconducting armchair SWCNTs with a distinctive BN line defect are studied, showing a super capacity to open the band gap of (4, 4) SWCNT to as large as 0.86 eV, while the opened band gap are found decreasing with the increasing diameters of SWCNTs. The opened band gap of SWCNTs can also be successfully modulated through both mechanical and electrical approaches by applying compressive uniaxial strain and electric field. This study provides novel insights into the large band gap opening and modulating of SWCNTs and could be useful in facilitating future applications of SWCNTs in electronic, optical and thermoelectric devices.

Radio Frequency Interference (RFI) suppression is an important technique in the ultra-wideband synthetic aperture radar (UWB SAR). In this paper, we mainly analyze the performance of a notch filter for RFI sup-pression. The theoretical output from notch filter is presented based on RFI signal’s narrowband property. The research conclusion shows that the notch filter has significant effect on sidelobes of the system response, which might be considered to be false targets, however it has little effect on the resolution of the system re-sponse. The theoretical result is verified by simulation and experimental data processing both in one dimen-sion (range dimension) and in two dimensions (range and azimuth dimension).

Though recommendation systems have been widely used for websites to generate new recommendations based on like-minded users’ preferences, IEEE Internet Computing points out that current system can not meet the real large-scale e-commerce demands, and has some weakness such as low precision and slow reaction. Huge personalized data are the key to successfully give a new recommendation, but they are difficultly dealt with for they are massive with high dimensional; addressing such problems, the paper suggests to use multi-layer feed-forward neural networks (MFNN) system based on case intelligence to partition massive personalized data into the most similar groups. The subsequent experiment indicates that our system model is constructive and understandable, and our algorithm can decrease the complexity of ANN algorithm, for which the system performance can be guaranteed.

How to suggest a valid recommend within a reasonable time is the greatest technical challenge for the recommendation system, for which tremendous user cases with high dimension are generated while it runs in real time, and these massive data are too difficult to compute directly. This paper proposes a case -intelligence system framework along with a feature -based multi -layer feed -forward neural networks (MFNN) to succeed case- retrieval based on dynamic computing, which constructs the neural networks dependence on the real input vectors instead of the fixed and dull networks structure presupposed, and can apply many kinds of knowledge granularity from various levels effectively to help users for information retrieval and case adaptation. Our subsequent experimental results indicate that it is capable of handling the massive personalized data, and our covering algorithm can decrease the complexity of MFNN algorithm for dynamic computing, which performs adaptable knowledge granularity to enhance the system's efficiency of reasoning.

Though many varieties of recommendation systems have been developed to greatly promote the intelligent level of E-commerce websites for recent years, IEEE Internet Computing points out that current system can not meet the real large-scale e-commerce demands", "and has some weakness such as low precision and slow reaction. The personalized recommendation system model based on case intelligence have proposed, which is a comprehensive expression with combination representation of human sense, logics and creativity, and can acquire the user's preferences from the former stored cases to satisfy the personalized needs. The paper focuses on how to perform effective demands on massive contents in websites, so rough sets (RS) and radial basis function network (RBF) techniques are selected to conquer problems caused by the large amounts of data. The new recommender firstly drills from the huge data in RS and reducts the main attributes, and then RBF retrieves the most valuable similar case for recommendation, which processes the same similar knowledge reasoning. The subsequent research indicates that the integrated system gives a fine performance as shown in our experiments.

Many web tools have been developed for information retrieval and information filtering to help users search, locate and manage web documents to find their needs, while IEEE Internet Computing points out that current system can not meet the real large-scale ecommerce demands, for the data from real websites is complex and multi-expression. Intelligent recommendation systems have been proposed to trace down to the acquirement of the personalized knowledge, whose system model suggests to acquire the user's preferences from the former stored cases to satisfy the personalized needs. So we select duplex techniques-rough sets (RS) and radial basis function network (RBF) - to conquer those problems caused by users' data, which are large in records, but rare in attributes. The subsequent research indicates that the newcomer can avoid sensitive to the noise along with the influence of irrelevant items, with which the results of our experiments for the validation on the proposed model are applausive.

Though the research in personalized recommendation systems has become widespread for recent years, IEEE Internet Computing points out that current system can not meet the real large-scale e-commerce demands, and has some weakness such as low precision and slow reaction. We have proposed a structure of personalized recommendation system based on case intelligence, which originates from human experience learning, and can facilitate to integrate various artificial intelligence components. Addressing on user case retrieval problem, the paper uses constructive and understandable multi-layer feed-forward neural networks (MFNN), and employs covering algorithm to decrease the complexity of ANN algorithm. Testing from the two different domains, our experimental results indicate that the integrated method is feasible for the processing of vast and high dimensional data, and can improve the recommendation quality and support the users effectively. The paper finally signifies that the better performance mainly comes from the reliable constructing MFNN.

This paper analyzes the SAR consecutive images formation for different trajectory selection and derives the range and azimuth geometric distortion induced by the trajectory deviation. Then a method is proposed for correcting the geometric distortion to form consecutive SAR images.

Through the wide use of E-commerce, the acquisition of personalized need is key to effective recommender. From the view of knowledge acquiring, case intelligence is a comprehensive expression which is integrated representation of human sense, logics and creativity, and can acquire the user's preferences from the former stored cases. As the E-commerce is under much complex conditions, this paper presents a personalized recommender based on case intelligence, which processes the same similar knowledge reasoning. Besides, compared with the most used collaborative filtering recommendation system, both the first user-based and the second item-based recommender, our system can be executing with the same similarity as their citing criteria. The article proposes a new reasoning structure integrated by various artificial intelligent technologies to acquire personalized knowledge. Finally, the case adaptation is described to explore the revision knowledge from huge cases through multi-channel accesses, which can guarantee the reliability and integrity of the adapting process.

The acquisition of personalized need is key to effective recommendation. Case intelligence is a comprehensive expression which is integrated representation of human sense, logics and creativity. Through the former cases we can acquire users' preferences which are implicit in case-base, the process of recommendation is easy to understand and accept. As E-commerce is in complex environment, cases are regarded as the foundation for knowledge representation in case intelligent system and may be represented in semi-structured or unstructured model, or even in natural language texts. This paper presents a personalized recommendation system based on case intelligence. The system has good flexibility, uses modular components to integrate various artificial intelligence technologies, which is convenient to acquire revision knowledge from huge cases from multi-channels. At last, this article proposes how to explore the revision knowledge and characteristic adaptation methods, so we can improve the quality of recommendation and “support” the users effectively.

As the size keeps increasing and applications keep developing, current Internet and TCP/IP are facing severe technical challenges. It is not secure, hard to use, and unpredictable. The shortages of architecture of current Internet have created barriers rather than stimulant to further developments. To resolve the problems of current Internet, this paper proposes a new type of non-layered network architecture, which is called Service Combination based Network Architecture.

This paper mainly introduces a high-performance system of real-time Ultra Wide-Band (UWB) SAR processing. Firstly, the sub-aperture Nonlinear Chirp Scaling (NCS) algorithm is optimized and selected to form the UWB SAR image, and then it is mapped to the Multiple Digital Signal Processor (Multi-DSP) board. Secondly, the timing sequence of the realtime processing is analyzed, and the processing time of each task is measured. Finally, the simulation result of the realtime UWB SAR processing is given. (4 pages)