catena-Poly[[[μ-cyanido-1:2κ2 C:N-tricyanido-1κ3 C-bis(ethylenediamine)-2κ4 N,N′-copper(II)iron(II)]-μ-cyanido-κ2 C:N-[bis(ethylenediamine-κ2 N,N′)copper(II)]-μ-cyanido-κ2 N:C] 4.5-hy­drate]

The asymmetric unit of the title compound, {[Cu2Fe(CN)6(C2H8N2)4]·4.5H2O}n, consists of two [Cu(C2H8N2)2]2+ cations, one [Fe(CN)6]4− anion, four water mol­ecules and a half water mol­ecule that lies on a twofold rotation axis. The FeII atom is coordinated by six C atoms from three terminal and three doubly bridging CN− ligands. The bridging CN− ligands connect the anion to a five-coordinate [Cu(C2H8N2)2]2+ cation and to two symmetry-related six-coordinate [Cu(C2H8N2)2]2+ cations, forming a one-dimensional polymer in the ab plane. Inter­molecular hydrogen bonds connect the polymer units into a three-dimensional network

Short-Term Truckload Spot Rates\u27 Prediction in Consideration of Temporal and Between-Route Correlations

Truckload spot rate (TSR), defined as a price offered on the spot to transport a certain cargo by using an entire truck on a target transportation line, usually price per kilometer-ton, is a key factor in shaping the freight market. In particular, the prediction of short-term TSR is of great importance to the daily operations of the trucking industry. However, existing predictive practices have been limited largely by the availability of multilateral information, such as detailed intraday TSR information. Fortunately, the emerging online freight exchange (OFEX) platforms provide unique opportunities to access and fuse more data for probing the trucking industry. As such, this paper aims to leverage the high-resolution trucking data from an OFEX platform to forecast short-term TSR. Specifically, a lagged coefficient weighted matrix-based multiple linear regression modeling (Lag-WMR) is proposed, and exogenous variables are selected by the light gradient boosting (LGB) method. This model simultaneously incorporates the dependency between historical and current TSR (temporal correlation) and correlations between the rates on alternative routes (between-route correlation). In addition, the effects of incorporating temporal and between-route correlations, time-lagged correlation and exogenous variable selection in modeling are emphasized and assessed through a case study on short-term TSR in Southwest China. The comparative results show that the proposed Lag-WMR model outperforms autoregressive integrated moving average (ARIMA) model and LGB in terms of model fitting and the quality and stability of predictions. Further research could focus on rates\u27 standardization, to define a practical freight index for the trucking industry. Although our results are specific to the Chinese trucking market, the method of analysis serves as a general model for similar international studies

Pharmaceutical approaches for COVID-19: An update on current therapeutic opportunities

SARS-CoV-2, a newly discovered coronavirus, has been linked to the COVID-19 pandemic and is currently an important public health issue. Despite all the work done to date around the world, there is still no viable treatment for COVID-19. This study examined the most recent evidence on the efficacy and safety of several therapeutic options available including natural substances, synthetic drugs and vaccines in the treatment of COVID-19. Various natural compounds such as sarsapogenin, lycorine, biscoclaurine, vitamin B12, glycyrrhizic acid, riboflavin, resveratrol and kaempferol, various vaccines and drugs such as AZD1222, mRNA-1273, BNT162b2, Sputnik V, and remdesivir, lopinavir, favipiravir, darunavir, oseltamivir, and umifenovir, resp., have been discussed comprehensively. We attempted to provide exhaustive information regarding the various prospective therapeutic approaches available in order to assist researchers and physicians in treating COVID-19 patients

An Ensemble Multilabel Classification for Disease Risk Prediction

It is important to identify and prevent disease risk as early as possible through regular physical examinations. We formulate the disease risk prediction into a multilabel classification problem. A novel Ensemble Label Power-set Pruned datasets Joint Decomposition (ELPPJD) method is proposed in this work. First, we transform the multilabel classification into a multiclass classification. Then, we propose the pruned datasets and joint decomposition methods to deal with the imbalance learning problem. Two strategies size balanced (SB) and label similarity (LS) are designed to decompose the training dataset. In the experiments, the dataset is from the real physical examination records. We contrast the performance of the ELPPJD method with two different decomposition strategies. Moreover, the comparison between ELPPJD and the classic multilabel classification methods RAkEL and HOMER is carried out. The experimental results show that the ELPPJD method with label similarity strategy has outstanding performance

Antibacterial characterization of Bacillus velezensis LG37 and mining of genes related to biosynthesis of antibacterial substances

Bacillus velezensis LG37 secretes various antibacterial substances and inhibits the growth of other bacteria. Here, we analyzed the antibacterial characteristics and the screening and verification of genes related to the synthesis of the antibacterial substance of LG37 by antibacterial activities experiment, Local BLAST+, and RT-PCR. LG37 was isolated from aquaculture water and preserved in our laboratory. The phylogenetic tree was used to analyze the genetic relationship between LG37 and the bacteriostatic test indicator strain. LG37 had a more substantial inhibitory effect on closely related strains, while the inhibitory effect on the more distantly related strains was weak. Combined with the results of genome sequencing, the ribosomal peptide (RP) bacteriocin gene and non-ribosomal peptide synthetase (NRPSs) related gene clusters were screened and analyzed. A total of six gene-coding RP bacteriocins and two genes coding surfactins and fengycin A NRPSs gene cluster were screened. Local BLAST+ analysis revealed a total of 11 NRPSs gene clusters. The active expression of the NRPSs and RP encoding genes was further validated by RT-PCR. The findings revealed various genes and gene clusters encoding RP bacteriocins and NRPSs in B. velezensis LG37. The bacterium is potentially valuable in diverse applications in aquaculture

A Phenomenological Thermal-Mechanical Viscoelastic Constitutive Modeling for Polypropylene Wood Composites

This paper presents a phenomenological thermal-mechanical viscoelastic constitutive modeling for polypropylene wood composites. Polypropylene (PP) wood composite specimens are compressed at strain rates from 10−4 to 10−2 s−1 and at temperature of , , and , respectively. The mechanical responses are shown to be sensitive both to strain rate and to temperature. Based on the Maxwell viscoelastic model, a nonlinear thermal-mechanical viscoelastic constitutive model is developed for the PP wood composite by decoupling the effect of temperature with that of the strain rate. Corresponding viscoelastic parameters are obtained through curve fitting with experimental data. Then the model is used to simulate thermal compression of the PP wood composite. The predicted theoretical results coincide quite well with experimental data. The proposed constitutive model is then applied to the thermoforming simulation of an automobile interior part with the PP wood composites

Effect of regenerator on the direct steam generation solar power system characterized by prolonged thermal storage and stable power conversion

The direct steam generation (DSG) solar power system using two stage accumulators and cascade steam-organic Rankine cycle (RC-ORC) has remarkably enlarged storage capacity. It can facilitate stable power generation and address the challenges of conventional DSG systems. Regenerator is generally an issue worthy of discussion in organic Rankine cycle (ORC) systems. However, its influence on the newly proposed DSG system has not been investigated yet and is expected to be appreciable. Introducing a regenerator affects not only the ORC efficiency, RC-ORC efficiency, heat exchanger area, but also heat storage capacity, discharge duration, discharge efficiency, aperture area of collectors and the net profit (ΔP). Detailed performance comparison between the DSG systems without/with regenerator is carried out in this paper. The results indicate that at a given power output, aperture area is reduced by the regenerator especially for MM, R365mfc and pentane due to the increment in ORC, RC-ORC and discharge efficiencies, as well as the decrement in heat input. Discharge duration is shortened by 0.01–1.78 h depending on ORC fluids. R365mfc exhibits the maximum ΔP (4.19∼6.48 million USD), followed by MM and pentane. On the contrary, ΔP is negative for benzene (−5.61∼-4.31 million USD)