Comparing Sales Strategies Using the Markov Chain Relationship Model

In this paper, the author applied the concept of the Markov chain and divided sales procedures into several indexes and states; use the state index for connecting success in sales and customer relations into Pfeifer’s method, establish a mathematical model, and demonstrate its result. In order to increase profits and decrease the cost of sales for the company, we further classify customers and propose different sale strategies. Case study and analysis are provided to elaborate the approach and its contribution to sales and CRM (customer relationship management) strategy

Absence of topological Hall effect in Fex_xRh100−x_{100-x} epitaxial films: revisiting their phase diagram

A series of Fe$_x$Rh$_{100-x}$ ($30 \leq x \leq 57$) films were epitaxially grown using magnetron sputtering, and were systematically studied by magnetization-, electrical resistivity-, and Hall resistivity measurements. After optimizing the growth conditions, phase-pure Fe$_{x}$Rh$_{100-x}$ films were obtained, and their magnetic phase diagram was revisited. The ferromagnetic (FM) to antiferromagnetic (AFM) transition is limited at narrow Fe-contents with $48 \leq x \leq 54$ in the bulk Fe$_x$Rh$_{100-x}$ alloys. By contrast, the FM-AFM transition in the Fe$_x$Rh$_{100-x}$ films is extended to cover a much wider $x$ range between 33 % and 53 %, whose critical temperature slightly decreases as increasing the Fe-content. The resistivity jump and magnetization drop at the FM-AFM transition are much more significant in the Fe$_x$Rh$_{100-x}$ films with $\sim$50 % Fe-content than in the Fe-deficient films, the latter have a large amount of paramagnetic phase. The magnetoresistivity (MR) is rather weak and positive in the AFM state, while it becomes negative when the FM phase shows up, and a giant MR appears in the mixed FM- and AFM states. The Hall resistivity is dominated by the ordinary Hall effect in the AFM state, while in the mixed state or high-temperature FM state, the anomalous Hall effect takes over. The absence of topological Hall resistivity in Fe$_{x}$Rh$_{100-x}$ films with various Fe-contents implies that the previously observed topological Hall effect is most likely extrinsic. We propose that the anomalous Hall effect caused by the FM iron moments at the interfaces nicely explains the hump-like anomaly in the Hall resistivity. Our systematic investigations may offer valuable insights into the spintronics based on iron-rhodium alloys.Comment: 9 pages, 10 figures; accepted by Phys. Rev.

Development and validation of platelet-to-albumin ratio as a clinical predictor for diffuse large B-cell lymphoma

IntroductionDiffuse large B-cell lymphoma (DLBCL) is the most common subtypes of lymphoma. Clinical biomarkers are still required for DLBCL patients to identify high-risk patients. Therefore, we developed and validated the platelet-to-albumin (PTA) ratio as a predictor for DLBCL patients.MethodsA group of 749 patients was randomly divided into a training set (600 patients) and an internal validation set (149 cases). The independent cohort of 110 patients was enrolled from the other hospital as an external validation set. Penalized smoothing spline (PS) Cox regression models were used to explore the non-linear relationship between the PTA ratio and overall survival (OS) as well as progression-free survival (PFS), respectively.ResultsA U-shaped relation between the PTA ratio and PFS was identified in the training set. The PTA ratio less than 2.7 or greater than 8.6 was associated with the shorter PFS. Additionally, the PTA ratio had an additional prognostic value to the well-established predictors. What’s more, the U-shaped pattern of the PTA ratio and PFS was respectively validated in the two validation sets.DiscussionA U-shaped association between the PTA ratio and PFS was found in patients with DLBCLs. The PTA ratio can be used as a biomarker, and may suggest abnormalities of both host nutritional aspect and systemic inflammation in DLBCL

A Memristive Diode Bridge-Based Canonical Chua’s Circuit

A novel memristor circuit is presented, which is generated from the canonical Chua’s circuit by replacing the Chua’s diode with a first order memristive diode bridge. The circuit dynamical characteristics with the variations of circuit parameters are investigated both theoretically and numerically. It can be found that the circuit has three determined equilibrium points, including a zero saddle point and two nonzero saddle-foci with index 2. Specially, the circuit is non-dissipative in the neighborhood of the zero saddle point, and there exists complex nonlinear phenomena of coexisting bifurcation modes and coexisting chaotic attractors. Experimental observations are performed to verify the numerical simulation results

Fairness-Aware Resource Allocation in Multi-Hop Wireless Powered Communication Networks with User Cooperation

In wireless powered communication networks (WPCNs), the harvested energy varies greatly among user nodes (UNs), resulting in throughput unfairness. Since the harvested energy is limited, each UN must strategically allocate the energy used for forwarding the other nodes’ information and for transmitting its own information, which further aggravates the global unfairness in terms of throughput. In this paper, we leverage user cooperation in multi-hop transmission to improve the throughput fairness. We formulate the fairness problem as the max-min throughput with resource allocation, which is NP-hard. We design an approximate algorithm to address this problem. The theoretical proof and the simulation results both show that the proposed algorithm provides tight upper and lower bounds for the optimal solution. Compared with the benchmark methods, our proposed method significantly enhances the throughput fairness for WPCNs

Characterization of the complete mitochondrial genome of Oryzaephilus surinamensis Linne (Insecta: Coleoptera: Silvanidae) from Xichuan

The saw-toothed grain beetle, Oryzaephilus surinamensis Linné, is a well-known stored-product insect. Beetles were obtained from Xichuan County and the mitochondrial genome was characterized (GenBank accession number MN535903). The mitogenome consists of a circular DNA molecule of 15,941 bp, with only 27.36% GC content. It comprises 13 protein-coding, 22 tRNA, and 2 rDNA genes. The protein-coding genes have typical ATN (Met) initiation codons and are terminated by typical TAN stop codons

Characterization of the complete mitochondrial genome of lesser grain borer Rhyzopertha dominica Fabricius (Insecta: Coleoptera: Bostrichidae) from Jingziguan

The lesser grain borer, Rhyzopertha dominica (Fabricius) is a primary pest of starch-containing stored products worldwide. Here, we report characterization of mitogenome of R. dominica and its phylogenetic position. Rhyzopertha dominica complete mitochondrial genome (GenBank accession number MN527959) from Jingziguan town consisted of a circular DNA molecule of 15,862 bp (with 74.36% A + T content). The mitogenome comprised of 13 protein-coding genes (PCGs), and 22 tRNA and two rRNA genes. PCGs had typical ATN (Met) initiation codons and were terminated by typical TAN stop codons

Novel Strategies Using Total Gastrodin and Gastrodigenin, or Total Gastrodigenin for Quality Control of Gastrodia elata

Gastrodia elata Blume (G. elata), a traditional Chinese medicine, is widely used for treatment of various neuro dysfunctions. However, its quality control is still limited to the determination of gastrodin. In the present study, two novel strategies based on quantitative evaluation of total gastrodin and gastrodigenin with base hydrolysis and total gastrodigenin with base-enzymatic hydrolysis followed by HPLC-FLD were put forward and successfully applied to evaluate the quality of 47 batches of G. elata from eight localities. Meanwhile, a systematic comparison of the novel strategy with the multiple markers and the Pharmacopeia method was performed. The results showed that the parishins category could be completely hydrolyzed to gastrodin by sodium hydroxide solution, and gastrodin could further utterly hydrolyze to gastrodigenin with β-d-glucosidase buffer solution. The contents of total gastrodin and gastrodigenin ranged from 1.311% to 2.034%, and total gastrodigenin from 0.748% to 1.120% at the eight localities. From the comparison, we can conclude that the two novel strategies can comprehensively reveal the characteristics of overall active ingredients in G. elata for quality control. The present study provides a feasible and credible strategy for the quality control of G. elata, suggesting a revision of the latest Chinese Pharmacopoeia or European Pharmacopoeia methods for the modernization of G. elata use

A Deep Learning Approach for Maximum Activity Links in D2D Communications

Mobile cellular communications are experiencing an exponential growth in traffic load on Long Term Evolution (LTE) eNode B (eNB) components. Such load can be significantly contained by directly sharing content among nearby users through device-to-device (D2D) communications, so that repeated downloads of the same data can be avoided as much as possible. Accordingly, for the purpose of improving the efficiency of content sharing and decreasing the load on the eNB, it is important to maximize the number of simultaneous D2D transmissions. Specially, maximizing the number of D2D links can not only improve spectrum and energy efficiency but can also reduce transmission delay. However, enabling maximum D2D links in a cellular network poses two major challenges. First, the interference between the D2D and cellular communications could critically affect their performance. Second, the minimum quality of service (QoS) requirement of cellular and D2D communication must be guaranteed. Therefore, a selection of active links is critical to gain the maximum number of D2D links. This can be formulated as a classical integer linear programming problem (link scheduling) that is known to be NP-hard. This paper proposes to obtain a set of network features via deep learning for solving this challenging problem. The idea is to optimize the D2D link schedule problem with a deep neural network (DNN). This makes a significant time reduction for delay-sensitive operations, since the computational overhead is mainly spent in the training process of the model. The simulation performed on a randomly generated link schedule problem showed that our algorithm is capable of finding satisfactory D2D link scheduling solutions by reducing computation time up to 90% without significantly affecting their accuracy