Joint Utilization Research Articles

High-efficient generation of natural killer cells from peripheral blood with preferable cell vitality and enhanced cytotoxicity by combination of IL-2, IL-15 and IL-18

Natural killer (NK) cells are pivotal effector lymphocytes characterized for the innate immune response to pathogenic microorganism and tumor cells without priming and sensitization. Despite emerging knowledge has highlighted the rosy prospects in tumor immunosurveillance, yet the large-scale clinical application of NK cell-based therapy is hindered largely attributes to the defects in generating sufficient and high-quality cellular products. Herein, on the basis of 16 kinds of candidate combinations, we investigated the feasibility of cytokine cocktail-based strategy for convenient and standardized NK cell cultivation as well as the multifaceted characteristics and cytotoxicity against tumor cells. Our results revealed that joint utilization of Interleukin (IL)-2, IL-15, IL-18 manifested the optimal facilitation upon the ex vivo expansion and proportion of NK cells in peripheral blood mononuclear cells (PBMCs). Meanwhile, the obtained NK cell population expressed high levels of activating molecules (CD16 and NKG2D) and exhibited splendid cytotoxicity against K562 cell line. Collectively, with the aid of cytokine-based programming, we established an alternative strategy for facilitating the large-scale persistence and activation of NK cells from peripheral blood, which would benefit the NK cell- and chimeric antigen receptor-modified NK (CAR-NK) cell-based autologous or allogeneic tumor immunotherapy.

Using an ETWatch (RS)-UZF-MODFLOW Coupled Model to Optimize Joint Use of Transferred Water and Local Water Sources in a Saline Water Area of the North China Plain

In the saline water area of our research, deep groundwater was over-pumped for agricultural irrigation which resulted in a decline of the deep groundwater level and an increase in the shallow groundwater table. Soil salination was also aggravated due to the strong evapotranspiration (ET) in the shallow groundwater areas, where ET removes water vapor from the unsaturated zone (ETu), and the groundwater (ETg). Joint utilities of multiple water sources of transferred water and local shallow and deep groundwater are essential for reasonable management of irrigation water. However, it is still difficult to distinguish ETu and ETg in coupled management of unsaturated zone and groundwater, which account for the water balance in utilities of multiple water sources in a regional scale. In this paper, we used an RS-based ETWatch model as a source of evapotranspiration data coupled with UZF-MODFLOW, an integrated hydrological model of the unsaturated–saturated zone, to estimate the ETg and ETu on a regional scale. It was shown that the coupled model (ETWatch-UZF-MODFLOW) avoids the influence of ETu on the groundwater balance calculation and improves the accuracy of the groundwater model. The model was used in the simulation and prediction of groundwater level. The eastern North China Plain (NCP) was selected as the study area where shallow groundwater was saline water and deep groundwater cone existed. We compared four different scenarios of irrigation methods, including current irrigation scenario, use of saline water, limited deep groundwater pumping, use of multiple water sources of transferred water and local groundwater. Results indicate that the total ETg for the four scenarios in the study area from 2013 to 2030 is 119 × 108 m3, 81.9 × 108 m3, 85.0 × 108 m3, and 92.3 × 108 m3, respectively, and the proportion of ETg to total ET was 6.85%, 4.79%, 4.97%, 5.37%. However, in regions where the groundwater depth is less than 3 m, ETg accounts for 12% of the total ET, indicating that groundwater was one of the main sources of evapotranspiration in shallow groundwater depth area.

Modeling ride requests and altruism in a socially connected dock-less vehicle sharing system

Dock-less vehicle sharing systems have become a norm in cities in recent years. However, a user often cannot find a vehicle near her location. In this study, we analyze the role of users’ route alteration on system performance, and whether altruism and expectation of performance improvement may change the way people use those systems. Since some transparency of other users’ preferences are needed in order for meaningful alternate routes, we propose to use a ride request mechanism. We argue that if implemented, this mechanism would result in a higher joint utility of users. We tested the model with computer simulations which supported the concept of improving joint utility by altruistic route alteration in random settings.

A source of thermal energy for roasting phosphogypsum – incinerators flue gas

The existing technologies for phosphogypsum utilization during its handling into building materials have been analyzed. Functioning equipment for joint utilization of municipal solid waste and phosphogypsum has been presented. An additional product of the installation, in addition to electrical and thermal energy, is gypsum. The waste gases from the incinerator are a heat source for roasting phosphogypsum. Fuel for the handling of phosphogypsum into gypsum is not used. A methodology for determining the specific amount of gases from a waste incinerator required for roasting phosphogypsum has been described in the article. The quantitative indicators for the reduction of polluting gases during the joint utilization of two waste types compared with operating independently waste treatment have been presented.

Utilization of the Cancer Medications Enquiry Database (CanMED)-National Drug Codes (NDC): Assessment of Systemic Breast Cancer Treatment Patterns

Cancer Medications Enquiry Database (CanMED) is comprised of two interactive, nomenclature-specific databases within the Observational Research in Oncology Toolbox: CanMED-Healthcare Common Procedure Coding System (HCPCS) and CanMED-National Drug Code (NDC), described through this study. CanMED includes medications with a) a US Food and Drug Administration-approved cancer treatment or treatment-related symptom management indication, b) inclusion in treatment guidelines, or c) an orphan drug designation. To demonstrate the joint utility of CanMED, medication codes associated with female breast cancer treatment were identified and utilization patterns were assessed within Surveillance Epidemiology and End Results-Medicare (SEER) data. CanMED-NDC (11_2018 v.1.2.4) includes 6860 NDC codes: chemotherapy (1870), immunotherapy (164), hormone therapy (3074), and ancillary therapy (1752). Treatment patterns among stage I-IIIA (20701) and stage IIIB-IV (2381) breast cancer patients were accordant with guideline-recommended treatment by stage and molecular subtype. CanMED facilitates identification of medications from observational data (eg, claims and electronic health records), promoting more standardized and efficient treatment-related cancer research.

Synergetic recycling of waste glass and recycled aggregates in cement mortars: Physical, durability and microstructure performance

The generation of large quantities of waste glass and construction waste has increasingly become an environmental burden in city governments. This study investigated the joint utilization of recycled glass cullet (RGC) and recycled fine aggregates (RFA) in cement mortars. The mechanical, durability and microstructure properties of the cement mortars were evaluated. The experimental results showed that the synergetic reuse of RGC and RFA in cement mortars was feasible both from mechanical and durability points of view. The replacement of RGC by RFA was beneficial to enhancing the compressive strength of cement mortars due to the improvement of the interfacial transition zone and microhardness of the paste matrix, and the refinement of the pore structures. Encouragingly, the combined use of RGC and RFA in cement mortars could exhibit low drying shrinkage and alkali-silica reaction expansion. In particular, the acid resistance of the cement mortars was improved effectively when the RGC was used in conjunction with RFA as 100% fine aggregates in the mortars.

Corporate Social Responsibility and Corporate Performance: A Hybrid Text Mining Algorithm

Until now, the works regarding the relationships between corporate operating performance and corporate social responsibility (CSR) could not reach a conclusive result (positive, natural, and negative). This circumstance can be attributed to two main reasons: (1) inadequate performance measurement and (2) ignoring the multi-dimensional nature of CSR. To combat this, we provided a hybrid decision framework that consisted of two main procedures: (1) performance measurement via linear programming algorithm and (2) CSR’s multi-dimensional nature extraction via text mining. By joint utilization of a linear programming algorithm and text mining, we could gain more insights from the outcome. The proposed decision framework, tested by real cases, is a promising alternative method for performance prediction. Managers can take this model as a roadmap and allocate resources to suitable places, as well as reach the goal of sustainable development.

Strategies for Design of Potential Singlet Fission Chromophores Utilizing a Combination of Ground-State and Excited-State Aromaticity Rules.

Singlet exciton fission photovoltaic technology requires chromophores with their lowest excited states arranged so that 2E(T1) < E(S1) and E(S1) < E(T2). Herein, qualitative theory and quantum chemical calculations are used to develop explicit strategies on how to use Baird’s 4n rule on excited-state aromaticity, combined with Hückel’s 4n + 2 rule for ground-state aromaticity, to tailor new potential chromophores for singlet fission. We first analyze the E(T1), E(S1), and E(T2) of benzene and cyclobutadiene (CBD) as excited-state antiaromatic and aromatic archetypes, respectively, and reveal that CBD fulfills the criteria on the state ordering for a singlet fission chromophore. We then look at fulvenes, a class of compounds that can be tuned by choice of substituents from Baird-antiaromatic to Baird-aromatic in T1 and S1 and from Hückel-aromatic to Hückel-antiaromatic in S0. The T1 and S1 states of most substituted fulvenes (159 of 225) are described by singly excited HOMO → LUMO configurations, providing a rational for the simultaneous tuning of E(T1) and E(S1) along an approximate (anti)aromaticity coordinate. Key to the tunability is the exchange integral (KH,L), which ideally is constant throughout the compound class, providing a constant ΔE(S1 – T1). This leads us to a geometric model for the identification of singlet fission chromophores, and we explore what factors limit the model. Candidates with calculated E(T1) values of ∼1 eV or higher are identified among benzannelated 4nπ-electron compound classes and siloles. In brief, it is clarified how the joint utilization of Baird’s 4n and Hückel’s 4n + 2 rules, together with substituent effects (electronic and steric) and benzannelation, can be used to tailor new chromophores with potential use in singlet fission photovoltaics.

Impact of Surface Albedo Assimilation on Snow Estimation

Surface albedo has a significant impact in determining the amount of available net radiation at the surface and the evolution of surface water and energy budget components. The snow accumulation and timing of melt, in particular, are directly impacted by the changes in land surface albedo. This study presents an evaluation of the impact of assimilating Moderate Resolution Imaging Spectroradiometer (MODIS)-based surface albedo estimates in the Noah multi-parameterization (Noah-MP) land surface model, over the continental US during the time period from 2000 to 2017. The evaluation of simulated snow depth and snow cover fields show that significant improvements from data assimilation (DA) are obtained over the High Plains and parts of the Rocky Mountains. Earlier snowmelt and reduced agreements with reference snow depth measurements, primarily over the Northeast US, are also observed due to albedo DA. Most improvements from assimilation are observed over locations with moderate vegetation and lower elevation. The aggregate impact on evapotranspiration and runoff from assimilation is found to be marginal. This study also evaluates the relative and joint utility of assimilating fractional snow cover and surface albedo measurements. Relative to surface albedo assimilation, fractional snow cover assimilation is found to provide smaller improvements in the simulated snow depth fields. The configuration that jointly assimilates surface albedo and fractional snow cover measurements is found to provide the most beneficial improvements compared to the univariate DA configurations for surface albedo or fractional snow cover. Overall, the study also points to the need for improving the albedo formulations in land surface models and the incorporation of observational uncertainties within albedo DA configurations.

Self-Supported Fe–N–C Electrocatalyst via Pyrolysis of EDTAFeNa Adsorbed on SBA-15 for the Oxygen Reduction Reaction

Self-supported Fe–N–C materials, without a carbon support and iron salt, were prepared via pyrolysis of a sole sodium ferric EDTA (EDTAFeNa) precursor containing C, N, and Fe atoms infused into hard template SBA-15, followed by base and acid etching and final heat treatment. The resultant EDTAFeNa-AL-HT2(SBA-15) demonstrated a four-electron pathway for the oxygen reduction reaction (ORR) in 0.1 M KOH with onset (Eonset) and half-wave (E1/2) potentials of 0.96 and 0.83 V versus RHE, respectively, closely matching those of benchmark Pt/C catalysts. The joint utilization of SBA-15 and etching endowed the self-supported Fe–N–C catalyst with high graphitization, moderate nitrogen doping, large surface area, hierarchical mesopores, and noncrystalline active Fe species with increased exposure over abundant pores, which synergistically enhanced ORR catalysis, giving rise to remarkable activity and selectivity while excluding contributions of crystalline Fe entities.

Multimodal Affective State Assessment Using fNIRS + EEG and Spontaneous Facial Expression.

Human facial expressions are regarded as a vital indicator of one’s emotion and intention, and even reveal the state of health and wellbeing. Emotional states have been associated with information processing within and between subcortical and cortical areas of the brain, including the amygdala and prefrontal cortex. In this study, we evaluated the relationship between spontaneous human facial affective expressions and multi-modal brain activity measured via non-invasive and wearable sensors: functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) signals. The affective states of twelve male participants detected via fNIRS, EEG, and spontaneous facial expressions were investigated in response to both image-content stimuli and video-content stimuli. We propose a method to jointly evaluate fNIRS and EEG signals for affective state detection (emotional valence as positive or negative). Experimental results reveal a strong correlation between spontaneous facial affective expressions and the perceived emotional valence. Moreover, the affective states were estimated by the fNIRS, EEG, and fNIRS + EEG brain activity measurements. We show that the proposed EEG + fNIRS hybrid method outperforms fNIRS-only and EEG-only approaches. Our findings indicate that the dynamic (video-content based) stimuli triggers a larger affective response than the static (image-content based) stimuli. These findings also suggest joint utilization of facial expression and wearable neuroimaging, fNIRS, and EEG, for improved emotional analysis and affective brain–computer interface applications.

Effluent lipopolysaccharide is a prompt marker of peritoneal dialysis-related gram-negative peritonitis.

To investigate the value of effluent lipopolysaccharide (LPS) for early detection of gram-negative peritonitis (GNP) in peritoneal dialysis (PD) patients. PD-related peritonitis episodes occurring between January 2016 and December 2018 were included in the study. Effluent LPS and the other infectious parameters were measured at peritonitis presentation, and peritonitis was categorized as GNP, non-GNP, and culture-negative peritonitis. Receiver operating characteristic (ROC) analysis was employed to evaluate the efficacy of effluent LPS to distinguish GNP. A total of 161 peritonitis episodes were analyzed, including 49 GNP episodes and 82 non-GNP episodes. In contrast with non-GNP, GNP presented with higher effluent leukocyte count (3236 (1497-6144) vs. 1904 (679-4071) cell mm-3, p = 0.008), increased effluent LPS (1.552 (0.502-2.500) vs. 0.016 (0.010-0.030) EU mL-1, p < 0.001), lower blood leukocyte count (9.95 ± 3.18 vs. 11.56 ± 4.37 × 109 L-1, p = 0.017), greater neutrophil predominance (87.1 ± 4.6% vs. 83.4 ± 7.7%, p = 0.001), and greater "procalcitonin" (PCT, 4.90 (2.20-12.60) vs. 1.00 (0.51-4.07) µg L-1, p < 0.001). It took 5.2 ± 3.1 h to report the results of effluent LPS. Effluent LPS cutoff value of >0.035 EU mL-1 showed an area under the ROC curve of 0.972 (95% CI 0.951-0.994, p < 0.001) in differentiating GNP from non-GNP with a sensitivity of 100% and a specificity of 80.5%, and its joint utilization with PCT further increased the specificity (91.4%) to discriminate GNP. PD effluent LPS could be an applicable early marker of gram-negative organism-related peritonitis in PD patients.

Joint utility optimization for wireless sensor networks with energy harvesting and cooperation

In wireless sensor networks (WSNs), the limited battery capacity restricts the lifetime of the sensor nodes and thus degrades the system performance. The energy harvesting and cooperation techniques are promising solutions to prolonging the battery life, by collecting energy from ambient environment and exchanging energy among sensor nodes. This paper studies the joint utility maximization problem for WSNs in consideration of energy harvesting and cooperation. We first derive an upper bound on the Lyapunov drift for the network stability, and then formulate the optimization as a stochastic optimization problem. Furthermore, we propose an energy harvesting and energy transfer, data transmission, power control, routing and scheduling (EDPR) online algorithm by combining Lyapunov optimization technique with drift-plus-penalty method and perturbation technique. It contributes to optimal utility in a distributed manner along with a balanced trade-off between network utility and queue backlog, with no need for any statistical information about dynamic systems and no concern of curse of dimensionality under large queue backlog. Simulation results also show the practicality of the proposed algorithm in real implementation since data transmission has a linear relationship with battery life.

Optimal stop-loss reinsurance with joint utility constraints

<p style='text-indent:20px;'>We investigate the optimal reinsurance problems in this paper, specifically, the stop-loss strategies that can bring mutual benefit to both the insurance company and the reinsurance company. The utility improvement constraints are adopted by both contracting parties to guarantee that a reinsurance contract will bring higher expected utilities of wealth to the two participants. We also introduce five risk criteria that reflect the interests of both parties. Under each optimality criterion, we obtain explicit expressions of optimal stop-loss retentions and the corresponding optimised value of objective functions. The upper and lower bounds of expected utility increments under the optimal stop-loss retentions are provided. In the numerical example, we analyse the expected utility improvements under the criterion of minimising total Value-at-Risk. Notable increases in the lower bound of total utility increments are observed after adopting the joint utility improvement constraints.

Financial bootstrapping among Costa Rican small businesses: an exploratory study

This study identifies and analyzes the financial bootstrapping techniques commonly used by small businesses in Costa Rica. The empirical application uses a unique sample of 161 Costa Rican SMEs for 2017. The results of the parallel factor analysis reveal that the analyzed SMEs adopt different types of bootstrapping techniques primarily related to the owners, customers, and alliances that facilitate the joint utilization of facilities and other assets. Entrepreneurs bootstrap their businesses to reduce the reliance on external financing. In this sense, the results of this study show that, rather than simply using what entrepreneurs are familiar with (e.g., credit from family or friends), Costa Rican small business managers are exploring and actively using a wide array of alternative methods in order to access financial resources.

Перспективы реализации транзитного потенциала РФ и Казахстана

Russia and Kazakhstan’s membership in the Eurasian Economic Union (EAEU) has symbolized a new era of history of strategic partnership of the two now focused on economic diversification and modernization. The aim of the article is to reveal current trends, stumbling points and prospects of Russia-Kazakhstan joint utilization of transit potential in East–West and North–South international transport corridors. The research hypothesis is that cooperation between Moscow and Nur–Sultan in transit sphere might lead to an increase in the overall efficiency of economic integration within the EAEU, as well as serve as a springboard for greater transcontinental connectivity. As of today, lack of supranational transport policy in the EAEU logically breeds competition between Russia and Kazakhstan for transit flows in the East–West corridor. Thus, Kazakhstan’s railway route in China–Europe direction holds a number of comparative advantages, i.e. shorter delivery dates and cheaper freight rates than that via Russia. However, being a steadfast of deepening economic integration in the EAEU, for instance, with the aim of creation of common transport and logistics market by 2025 might force Nur–Sultan to meet Moscow’s halfway. The article concludes that in order to inclusively exploit their transit potential Russia and Kazakhstan should work out a number of collective transit-stimulating initiatives, i.e. common railway transit rates and digital systems of tracking, at the level of the Eurasian Economic Commission.

Incentivizing Mobile Video Users With Data Sponsoring and Edge Caching

Recently, edge caching has emerged as a new data sponsoring scheme, where the devices on the edge network, e.g., 4G/5G base stations, cache video contents and directly delivery them to mobile video users. Such caching schemes have significantly decreased the backhaul congestion, reduce the delivery latency, thus attract more mobile video users and monetize a huge number of videos. In this paper, we consider a hybrid caching schemes system, which combines edge cache sponsoring (ECS) and traditional cellular data sponsoring (CDS), where the content providers display advertisements to mitigate the cellular data downloading expense and provide attractive contents for mobile video users. In the system, we investigate the cooperative scenario and the competitive scenario between the two sponsoring schemes, and a mobile video user can select one scheme or neither of them for the requests of a video. In the first scenario, we focus on achieving the maximal total benefit of content providers by optimizing CDS and ECS schemes together. In the second scenario, we separately optimize ECS and CDS schemes and maximize the benefits of corresponding content providers. To illustrate the effectiveness of the two scenarios, we formulate the system as a two-stage game: 1) in the first stage, content providers (i.e., leaders) choose the sponsor effort in sponsor schemes (cooperatively or competitively); 2) in the second stage, mobile video users (i.e., followers) select their sponsor preferences. We conduct numerical results to explore the sub-game perfect equilibrium and find that the joint utilization of the two sponsor schemes can benefit the mobile video users, i.e., when ECS and CDS compete with each other, MUs can benefit 36% ~ 140% more than the case where there exists only one sponsor scheme. While when CPs cooperate with each other, their total payoff is maximized, the mobile video users' payoff also increases. Moreover, we find that ECS can benefit the content providers more than CDS when sponsor revenue is high, and this indicates that ECS is a promising sponsor scheme for the high-value contents.

Risk-Sensitive Task Fetching and Offloading for Vehicular Edge Computing

This letter studies an ultra-reliable low latency communication problem focusing on a vehicular edge computing network in which vehicles either fetch and synthesize images recorded by surveillance cameras or acquire the synthesized image from an edge computing server. The notion of risk-sensitive in financial mathematics is leveraged to define a reliability measure, and the studied problem is formulated as a risk minimization problem for each vehicle's end-to-end (E2E) task fetching and offloading delays. Specifically, by resorting to a joint utility and policy estimation-based learning algorithm, a distributed risk-sensitive solution for task fetching and offloading is proposed. Simulation results show that our proposed solution achieves performance improvements up to 40% variance reduction and steeper distribution tail of the E2E delay over an averaged-based baseline.

Diagnostic performance of serum cystatin C and complement component 1q in lupus nephritis

BackgroundThe information concerning non-invasive, easily obtainable, and accurate biomarkers for diagnosis of lupus nephritis (LN) is extremely limited. The aim of this study was to evaluate the diagnostic performance of cystatin C (CysC) and complement component 1q (C1q) for LN.MethodsA case-control study that included 905 patients with systemic lupus erythematosus (SLE) without LN (group SLE), 334 patients with active lupus nephritis (group LNA), 255 patients with inactive lupus nephritis (group LNI), and 497 healthy individuals (group HC) was performed in Mianyang Central Hospital from March 2017 to December 2018. The serum levels of CysC, C1q, urea (Urea), and creatinine (Creat) were measured, and 2 estimated glomerular filtration rates (eGFRCysC and eGFRCreat) were calculated by equations which were based on serum CysC established by our group and the modification of diet in renal disease (MDRD), respectively. ANOVA analysis or Kruskal-Wallis test was used for comparing the differences among the groups, and receiver operating characteristic (ROC) curve was applied to identify the diagnostic efficiencies of individual or combined multiple indicators.ResultsSignificantly elevated CysC and decreased C1q were observed in the LNA and LNI groups, which was in contrast to their levels in the SLE and HC groups. CysC (AUC = 0.906) or eGFRCysC (AUC = 0.907) assessed the highest diagnostic performance on LNA when detected individually, followed by C1q (AUC = 0.753). Joint utilization of C1q and CysC achieved very good performance (AUC = 0.933) which approximated to the best one observed in the combinations of C1q, Urea, CysC, eGFRCreat, and Creat (AUC = 0.975).ConclusionThe separately detected CysC (eGFRCysC) and C1q were superior to the conventional biomarkers Urea, Creat, and eGFRCreat in the diagnosis of LNA. Moreover, although the combined detection of Urea, Creat, C1q, CysC, and eGFRCreat had the greatest diagnostic performance, the joint utilization of CysC and C1q could be prioritized for rapid discrimination of LNA if the economic burden is taken into consideration.

NEWS-BASED SOFT INFORMATION AS A CORPORATE COMPETITIVE ADVANTAGE

This study establishes a decision-making conceptual architecture that evaluates decision making units (DMUs) from numerous aspects. The architecture combines financial indicators together with a variety of data envelopment analysis (DEA) specifications to encapsulate more information to give a complete picture of a corporate’s operation. To make outcomes more accessible to non-specialists, multidimensional scaling (MDS) was performed to visualize the data. Most previous studies on forecasting model construction have relied heavily on hard information, with quite a few works taking into consideration soft information, which contains much denser and more diverse messages than hard information. To overcome this challenge, we consider two different types of soft information: supply chain influential indicator (SCI) and sentimental indicator (STI). SCI is computed by joint utilization of text mining (TM) and social network analysis (SNA), with TM identifying the corporate’s SC relationships from news articles and SNA to determining their impact on the network. STI is extracted from an accounting narrative so as to comprehensively illustrate the relationships between pervious and future performances. The analyzed outcomes are then fed into an artificial intelligence (AI)-based technique to construct the forecasting model. The introduced model, examined by real cases, is a promising alternative for performance forecasting.