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Electricity consumption is an important economic index and plays a significant role in drawing up an energy development policy for each country. Multivariate techniques and time-series analysis have been proposed to deal with electricity consumption forecasting, but a large amount of historical data is required to obtain accurate predictions. The grey forecasting model attracted researchers by its ability to characterize an uncertain system effectively with a limited number of samples. GM(1,1) is the most frequently used grey forecasting model, but its developing coefficient and control variable were dependent on the background value that is not easy to be determined, whereas a neural-network-based GM(1,1) model called NNGM(1,1) has been presented to resolve this troublesome problem. This study has applied NNGM(1,1) to electricity consumption and has examined its forecasting ability on electricity consumption using sample data from the Turkish Ministry of Energy and Natural Resources and the Asia–Pacific Economic Cooperation energy database. Experimental results demonstrate that NNGM(1,1) performs well.

يتناول كتاب (ماوتسي يونج) وهو صاحب سيرة طويلة عبر ما يقرب من سبعين عاما، نشأ في ريف الصين لأب فلاح فقير، استهوته الماركسية فانتمى إليها، ثم صار أحد نجومها في الحزب الشيوعي الصيني، ثم صار رئيسا للحزب، ثم استقل بعرش الصين وجلس عليه حوالي ثلاثين عاما، قاد فيها الصين برؤيته الخاصة فصنع منها دولة قوية في وقت وجيز، ولا يزال كتابه الأحمر مرجعا أساسيا للفكر الصيني والسياسة الصينية، بل إن دواوين شعره هي الأكثر مبيعا في الصين، ولا تزال سيرته مقصد كثير من المطلعين.‪

Our study aimed to determine how lncRNA DANCR, miR-320a, and CTNNB1 interact with each other and regulate osteogenic differentiation in osteoporosis. qRT-PCR and western blotting were performed to determine the expression of DANCR, miR-320a, CTNNB1, and the osteoporosis- or Wnt/β-catenin pathway-related markers T-cell factor 1 (TCF-1), runt-related transcription factor 2 (RUNX2), alkaline phosphatase (ALP), osteocalcin (OCN), and osteopontin (OPN). Interactions between CTNNB1, DANCR, and miR-320a were predicted by bioinformatics approaches and validated using a luciferase assay. Osteoblastic phenotypes were evaluated by ALP staining, ALP activity assay and Alizarin Red staining. The bilateral ovariectomy method was used to establish an in vivo osteoporosis model. Bone morphological changes were examined using hematoxylin and eosin (H&E) and Alcian Blue staining. The expression levels of DANCR and miR-320a in BMSCs derived from osteoporosis patients were upregulated, whereas CTNNB1 expression was downregulated compared with that in healthy controls. Importantly, we demonstrated that miR-320a and DANCR acted independently from each other and both inhibited CTNNB1 expression, whereas the inhibitory effect was additive when miR-320a and DANCR were cooverexpressed. Moreover, we found that DANCR overexpression largely abrogated the effect of the miR-320a inhibitor on CTNNB1 expression and the Wnt/β-catenin signaling pathway in BMSCs during osteogenic differentiation. We further confirmed the results above in BMSCs derived from an osteoporosis animal model. Taken together, our findings revealed that DANCR and miR-320a regulated the Wnt/β-catenin signaling pathway during osteogenic differentiation in osteoporosis through CTNNB1 inhibition. Our results highlight the potential value of DANCR and miR-320a as promising therapeutic targets for osteoporosis treatment.Osteoporosis: Tiny targets to keep bones strongTwo non-coding RNAs are potential targets for reducing bone loss in post-menopausal osteoporosis. Bones are constantly being remodeled; when resorption outpaces generation of new bone, bones are weakened, causing osteoporosis and leading to decreased quality of life and injuries. Although treatments exist, they often have undesirable side effects, and new treatments are needed. The molecular basis of the changes that accompany osteoporosis are poorly understood. Da Zhong at the Xiangya Hospital of Central South University in Changsha, China, and co-workers investigated how two non-coding RNAs, small molecules that regulate gene expression, are involved in the progression of post-menopausal osteoporosis. They found that levels of both molecules are increased in osteoporosis, and that silencing them increases building of new bone, key to maintaining bone strength. These results illuminate a potential new direction in treatments for osteoporosis.

Background 3-Hydroxy butyrate dehydrogenase 2 (BDH2) is a short-chain dehydrogenase/reductase family member that plays a key role in the development and pathogenesis of human cancers. However, the role of BDH2 in gastric cancer (GC) remains largely unclear. Our study aimed to ascertain the regulatory mechanisms of BDH2 in GC, which could be used to develop new therapeutic strategies. Methods Western blotting, immunohistochemistry, and RT-PCR were used to investigate the expression of BDH2 in GC specimens and cell lines. Its correlation with the clinicopathological characteristics and prognosis of GC patients was analysed. Functional assays, such as CCK-8 and TUNEL assays, transmission electron microscopy, and an in vivo tumour growth assay, were performed to examine the proliferation, apoptosis, and autophagy of GC cells. Related molecular mechanisms were clarified by luciferase reporter, coimmunoprecipitation, and ubiquitination assays. Results BDH2 was markedly downregulated in GC tissues and cells, and the low expression of BDH2 was associated with poor survival of GC patients. Functionally, BDH2 overexpression significantly induced apoptosis and autophagy in vitro and in vivo. Mechanistically, BDH2 promoted Keap1 interaction with Nrf2 to increase the ubiquitination level of Nrf2. Ubiquitination/degradation of Nrf2 inhibited the activity of ARE to increase accumulation of reactive oxygen species (ROS), thereby inhibiting the phosphorylation levels of Akt Ser473 and mTOR Ser2448 . Conclusions Our study indicates that BDH2 is an important tumour suppressor in GC. BDH2 regulates intracellular ROS levels to mediate the PI3K/Akt/mTOR pathway through Keap1/Nrf2/ARE signalling, thereby inhibiting the growth of GC.

Tourism demand forecasting has played an important role in supporting governments to devise development policies for travel and tourism. However, time series related to tourism often do not conform to statistical assumptions and feature significant temporal fluctuations. Because a Fourier series is often applied to oscillating sequences to remove noise, it is reasonable to develop a grey prediction model in conjunction with a Fourier series to forecast tourism demand. However, grey prediction models traditionally use one-order accumulation, treating each sample with equal weight, to identify regularities concealed in data sequences. Furthermore, when generating residuals from Fourier series, the prediction accuracy of the newly generated predicted values is not taken into account. In this study, by using fractional order accumulation to assign appropriate weights to samples, we propose a fractional grey prediction model with Fourier series that offers high prediction accuracy. Experimental results demonstrate that the proposed grey prediction model performs well compared with other considered prediction models.

Human infections with zoonotic coronaviruses (CoVs), including severe acute respiratory syndrome (SARS)-CoV and Middle East respiratory syndrome (MERS)-CoV, have raised great public health concern globally. Here, we report a novel bat-origin CoV causing severe and fatal pneumonia in humans. We collected clinical data and bronchoalveolar lavage (BAL) specimens from five patients with severe pneumonia from Wuhan Jinyintan Hospital, Hubei province, China. Nucleic acids of the BAL were extracted and subjected to next-generation sequencing. Virus isolation was carried out, and maximum-likelihood phylogenetic trees were constructed. Five patients hospitalized from December 18 to December 29, 2019 presented with fever, cough, and dyspnea accompanied by complications of acute respiratory distress syndrome. Chest radiography revealed diffuse opacities and consolidation. One of these patients died. Sequence results revealed the presence of a previously unknown β-CoV strain in all five patients, with 99.8% to 99.9% nucleotide identities among the isolates. These isolates showed 79.0% nucleotide identity with the sequence of SARS-CoV (GenBank NC_004718) and 51.8% identity with the sequence of MERS-CoV (GenBank NC_019843). The virus is phylogenetically closest to a bat SARS-like CoV (SL-ZC45, GenBank MG772933) with 87.6% to 87.7% nucleotide identity, but is in a separate clade. Moreover, these viruses have a single intact open reading frame gene 8, as a further indicator of bat-origin CoVs. However, the amino acid sequence of the tentative receptor-binding domain resembles that of SARS-CoV, indicating that these viruses might use the same receptor. A novel bat-borne CoV was identified that is associated with severe and fatal respiratory disease in humans.

Background: There is controversy over whether use of new oral anticoagulants (NOACs) associates with increased hemorrhage risk compared with non-NOAC. Meanwhile, determining which NOAC to use remains unclear. We aimed to summarize the evidence about NOACs in venous thromboembolism (VTE) prevention for patients with total hip and knee arthroplasty (THA and TKA). Methods: We searched RCTs assessing NOACs for VTE prophylaxis in adults undergoing THA and TKA in Medline, Embase, and Cochrane up to May 2021. Primary outcomes were VTE [included deep vein thrombosis (DVT) and pulmonary embolism (PE)], major VTE, and major bleeding. The rank probabilities of each treatment were summarized by the surface under the cumulative ranking curve area (SUCRA). Results: 25 RCTs with 42,994 patients were included. Compared with non-NOAC, NOACs were associated with a decreased risk of VTE (RR 0.68; 95% CI 0.55–0.84) and major VTE (RR = 0.52; 95% CI 0.35–0.76). Additionally, rivaroxaban, apixaban, and edoxaban but not dabigatran and betrixaban, did confer a higher efficacy compared with non-NOAC. None of the individual NOACs increased the risk of bleeding, while apixaban and betrixaban were even associated with a decreased risk of bleeding. In the comparison of different NOACs, rivaroxaban was associated with the greatest benefits in VTE (SUCRA = 79.6), DVT (SUCRA = 88.8), and major VTE (SUCRA = 89.9) prevention. Furthermore, subgroup analysis confirmed that NOACs associated with a higher efficacy tendency in patients with follow-up duration <60 days than follow-up duration ≥60 days. Conclusion: Evidence suggests that NOACs exert more benefits on VTE prophylaxis, and none of the individual NOACs increased hemorrhage compared with non-NOAC. Among various NOACs, rivaroxaban is recommended in patients with lower bleeding risk, and apixaban is recommended in patients with higher bleeding risk. Systematic Review Registration : [ https://www.crd.york.ac.uk/prospero/ ], identifier [CRD42021266890].

Lithium-ion batteries (LIBs) are at the forefront of energy storage and highly demanded in consumer electronics due to their high energy density, long battery life, and great flexibility. However, LIBs usually suffer from obvious capacity reduction, security problems, and a sharp decline in cycle life under low temperatures, especially below 0 °C, which can be mainly ascribed to the decrease in Li+ diffusion coefficient in both electrodes and electrolyte, poor transfer kinetics on the interphase, high Li+ desolvation barrier in the electrolyte, and severe Li plating and dendrite. Targeting such issues, approaches to improve the kinetics and stability of cathodes are also dissected, followed by the evaluation of the application prospects and modifications between various anodes and the strategies of electrolyte design including cosolvent, blended Li salts, high-concentration electrolyte, and additive introduction. Such designs elucidate the successful exploration of low-temperature LIBs with high energy density and long lifespan. This review prospects the future paths of research for LIBs under cold environments, aiming to provide insightful guidance for the reasonable design of LIBs under low temperature, accelerating their widespread application and commercialization.

Galactic short-period close white dwarf binaries (CWDBs) are important objects for space-borne gravitational-wave (GW) detectors in the millihertz frequency bands. Due to the intrinsically low luminosity, only about 25 identified CWDBs are detectable by the Laser Interferometer Space Antenna (LISA), which are also known as verification binaries (VBs). The Gaia Early Data Release 3 (EDR3) provids a catalog containing a large number of CWDB candidates, which also includes parallax and photometry measurements. We crossmatch the Gaia EDR3 and Zwicky Transient Facility public data release 8, and apply period-finding algorithms to obtain a sample of periodic variables. The phase-folded light curves are inspected, and finally we obtain a binary sample containing 429 CWDB candidates. We further classify the samples into eclipsing binaries (including 58 HW Vir-type binaries, 65 EA-type binaries, 56 EB-type binaries, and 41 EW-type binaries) and ellipsoidal variations (209 ELL-type binaries). We discovered four ultrashort period binary candidates with unique light-curve shapes. We estimate the GW amplitude of all of our binary candidates, and calculate the corresponding signal-to-noise ratio (S/N) for TianQin and LISA. We find two (six) potential GW candidates with S/Ns greater than 5 in the nominal mission time of TianQin (LISA), which increases the total number of candidate VBs for TianQin (LISA) to 18 (31).