Growth Probability Research Articles

Highly productive and robust core@shell HeatPath SiC-Al2O3 @Co/Re/Al2O3 catalyst for Fischer–Tropsch synthesis

Co-based catalysts are highly active for synthesizing long-chain paraffins through Fischer–Tropsch synthesis. However, their exothermic reactions can cause overheating and catalyst deactivation. To address this, thermally conductive SiC-Al2O3 pellets (HeatPath™) were coated with a Co/Re/Al2O3 shell, significantly boosting the CO conversion rate and the yield of C2–4 and C5+ hydrocarbons over a wide range of temperatures by dissipating the reaction heat. The core@shell HeatPath@Co/Re/Al2O3 catalyst demonstrated high productivity (up to 19.7 gCOgcat−1 h−1), exceptional long-term stability over 660 h time-on-stream, with high-temperature operation up to 260 °C, a low CH4 selectivity (7.1 %) and a chain growth probability (α) > 0.8. In contrast, the irreversible deactivation of a powder Co/Re/Al2O3 catalyst started at 195 °C, resulting in >60 % CH4 selectivity and ∼100 % CO conversion due to excessive local heat. The CO conversion rate on the core@shell catalyst could be further improved by increasing the H2/CO ratio and temperature, with commercially viable CH4 selectivity.

Two Significant Factors Affecting the Dimensions of the ZnO Nanorods During Chemical Bath Deposition: Precursor Solution Concentration and HMTA Content

The effects of zinc ion concentration and hexamethylene tetramine (HMTA) content of the aqueous precursor solution on the aspect ratios of the one-dimensional (1D) ZnO nanorods during chemical bath deposition (CBD) were investigated. The ZnO nanorods were grown on these seeded substrates by the low-temperature CBD method at 95 °C for 5 h. In the first part of this investigation the zinc nitrate hexahydrate (ZNH) to HMTA molar ratio was kept constant at a ratio of 1:1 for each of the CBD solutions prepared with different Zn^(+2) ion concentrations of 0.025, 0.035, 0.050, and 0.075 M. The number densities of the nanorods (i.e., number of nanorods per unit area) were increased with the increasing concentration. In the second part, the ZNH to HMTA molar ratio was varied to differ from the 1:1 value and, in turn, to obtain the precursor solutions relatively rich in Zn^(+2) or OH^-ions. Here, the concentration of the precursor solution was kept constant at 0.05 M. The lateral growth perpendicular to the c-axis of the ZnO nanorods was found to be suppressed with the increasing HMTA content (e.g., for the ZNH to HMTA molar ratio of 0.4: 1) due to its capping effect. However, the precursor solution containing an excessive amount of HMTA led to a decrease in the probability of crystal growth, which has been attributed to the OH^- ion enrichment.

Monitoring Waterlogging Damage of Winter Wheat Based on HYDRUS-1D and WOFOST Coupled Model and Assimilated Soil Moisture Data of Remote Sensing

Waterlogging harms winter wheat growth. To enable accurate monitoring of agricultural waterlogging, this paper conducts a winter wheat waterlogging monitoring study using multi-source data in Guzhen County, Anhui Province, China. The hydrological model HYDRUS-1D is coupled with the crop growth model WOFOST, and the Ensemble Kalman Filter is used to assimilate Sentinel-1 inversion soil moisture data. According to the precision and continuity of soil moisture, the damage of winter wheat waterlogging were obtained. The experimental results show that the accuracy of the soil moisture is improved after data assimilation compared with that before data assimilation, and the Nash–Sutcliffe efficiency (NSE) of the simulated soil moisture values at three monitoring sites increased from 0.528, 0.541 and 0.575 to 0.752, 0.692 and 0.731, respectively. A new waterlogging identification criterion has been proposed based on the growth periods and probability distribution of soil moisture. The proportion, calculated from this identification criterion, of the waterlogging wheat farmland in total farmland shows a high correlation with the yield reduction rate. The correlation coefficient of the waterlogging farmland proportion and the yield reduction rate in 11 towns of Guzhen County reaches 0.78. Through the synchronization of geography, agriculture and meteorology, the framework shows great potential in waterlogging monitoring.

Shelf-life boundaries of Listeria monocytogenes in cold smoked salmon during refrigerated storage and temperature abuse

Cold smoked salmon (CSS) is a high-value ready-to-eat product, but it generally has a short shelf-life even under refrigeration and can support the growth of Listeria monocytogenes. Therefore, the objective of this study was to examine the growth and survival of L. monocytogenes in CSS during refrigerated storage and temperature abuse.The growth and survival data of L. monocytogenes (116 records, 465 data points) were retrieved from ComBase (https://www.combase.cc). All records contained storage time and temperature, but other information (aw, pH, and salt) was not fully documented. Each data point, normalized with the initial population to calculate relative growth (RG, log CFU/g), was used to classify the probability of growth. Eighty percent (80%) of the data were randomly sampled for examining the effect of storage time and temperature on growth of L. monocytogenes, while the remaining 20% were set aside for model validation.Logistic regression was used to develop a model for classifying L. monocytogenes growth according to 7 different control thresholds (CT), ranging from 0 to 3 log CFU/g in RG. A probability threshold was set to judge if the bacterial growth has exceeded a CT. The validation showed > 89% of true negative rate for not exceeding the control thresholds. A dynamic method was then developed and demonstrated to predict the growth probabilities under fluctuating temperature conditions. The result of this study suggested that storage time and temperature could be used to predict the growth of L. monocytogenes in CSS and to control listeriosis using a risk-based strategy. It can be used by the retailers and consumers to determine if a packaged product is safe to consume based on its time and temperature history.

The synzootic potential of common epidemics in chamois populations

Southern chamois (Rupicapra pyrenaica) is a medium-sized and gregarious mountain ungulate with populations affected by periodic outbreaks of border disease virus (BD), infectious keratoconjunctivitis (IKC), and sarcoptic mange (SM). Even though the impact of each disease on chamois populations has been described in detail, there is a lack of information about the potential impact of concomitant epidemics and the synzootic potential (co-occurring enzootic or epizootic processes producing worse health outcomes in wildlife) on chamois populations. Furthermore, whether a specific order of apparition of epidemics is more or less harmful for the host population is practically unknown not only for chamois but also for most mammal populations. Using a population viability analysis (PVA), we studied the consequences of multiple disease outbreaks with synzootic potential on growth rates and probabilities of extinction of virtual populations exposed to hard winters, density dependence, and co-occurring BD, IKC, and SM outbreaks. Such infections are not under cross-immunity nor density-dependent processes and thus are supposed to affect population demography independently. Heavy snowfalls are also likely to occur in our simulated populations. Our simulations showed that a second outbreak, even caused by a low virulent pathogen, causes an increase in the probability of extinction of the host population with regard to the first outbreak. IKC-BD- and SM-BD-affected populations had a higher risk of becoming extinct in 50 years confirming the extra risk of multiple outbreaks on the viability of the affected populations.

Combining modeling with novel field observations yields new insights into wintertime food limitation of larval fish

AbstractRecruitment success of marine fishes is generally considered to be highly dependent on larval growth and survival. In temperate ecosystems, fish larvae are sensitive to food limitation during the low productivity seasons, particularly if water temperatures and concomitant larval metabolic costs increase due to climate change. We combined 7 years of in situ sampling of larval fish, novel observations on zooplankton via automated image analyses, and larval physiological modeling to explore feeding conditions of Atlantic herring larvae (Clupea harengus) in the North Sea. The observed plankton size‐structure was close to the theoretical optimum for larval foraging, but not the biomass. Our results for autumn larvae supported Hjort's critical period hypothesis: small first‐feeding larvae were predicted to have a high probability of starvation, whereas larvae > 13 mm were able to reach their maximal growth capacity. In winter, the majority of herring larvae of all tested sizes (5–27 cm) experienced food‐limitation with over 35% probability of starvation. Sensitivity analysis suggested that young herring larvae improve their growth performance and probability of survival if feed not only on copepods and their life‐stages but include other microplankters in their diet. Given projected warming of the North Sea, our model predicts that herring larvae would require 28% (35%) more prey biomass in autumn (winter) to sustain their growth and survival in the future. This finding together with the ongoing low recruitment of North Sea herring underscore the importance of future micro‐ and mesoplankton monitoring within a scope of wintertime larval fish surveys.

Natural history of non-functioning pituitary microadenomas: results from the UK non-functioning pituitary adenoma consortium.

The optimal approach to the surveillance of non-functioning pituitary microadenomas (micro-NFPAs) is not clearly established. Our aim was to generate evidence on the natural history of micro-NFPAs to support patient care. Multi-centre, retrospective, cohort study involving 23 endocrine departments (UK NFPA consortium). Clinical, imaging, and hormonal data of micro-NFPA cases between January, 1, 2008 and December, 21, 2021 were analysed. Data for 459 patients were retrieved [median age at detection 44 years (IQR 31-57)-152 males/307 females]. Four hundred and nineteen patients had more than two magnetic resonance imagings (MRIs) [median imaging monitoring 3.5 years (IQR 1.71-6.1)]. One case developed apoplexy. Cumulative probability of micro-NFPA growth was 7.8% (95% CI, 4.9%-8.1%) and 14.5% (95% CI, 10.2%-18.8%) at 3 and 5 years, respectively, and of reduction 14.1% (95% CI, 10.4%-17.8%) and 21.3% (95% CI, 16.4%-26.2%) at 3 and 5 years, respectively. Median tumour enlargement was 2 mm (IQR 1-3) and 49% of micro-NFPAs that grew became macroadenomas (nearly all >5 mm at detection). Eight (1.9%) patients received surgery (only one had visual compromise with surgery required >3 years after micro-NFPA detection). Sex, age, and size at baseline were not predictors of enlargement/reduction. At the time of detection, 7.2%, 1.7%, and 1.5% patients had secondary hypogonadism, hypothyroidism, and hypoadrenalism, respectively. Two (0.6%) developed hypopituitarism during follow-up (after progression to macroadenoma). Probability of micro-NFPA growth is low, and the development of new hypopituitarism is rare. Delaying the first follow-up MRI to 3 years and avoiding hormonal re-evaluation in the absence of tumour growth or clinical manifestations is a safe approach for micro-NFPA surveillance.

Transient population dynamics drive the spread of invasive wild pigs and reveal impacts of management in North America

Invasion of nonindigenous species is considered one of the most urgent problems affecting native ecosystems and agricultural systems. Mechanistic models that account for short-term population dynamics can improve prediction because they incorporate differing demographic processes that link the environmental conditions of a spatial location explicitly with the invasion process. Yet short-term population dynamics are rarely accounted for in spatial models of invasive species spread.Accounting for transient (short-term) population dynamics that arise from the interaction of age structure and vital rates, we predict the stochastic population growth rate and establishment probability of wild pigs following introduction into any location in North America. Established ecological theory suggests that the rate of spatial spread is proportional to population growth rate. Using observed geographic distribution data for wild pigs we calculated geographic spread rates (watersheds/year) from 1982 to 2021. We investigated if observed spread rates increased in watersheds with higher stochastic population growth rates. Stochastic population growth rate and establishment probability of wild pigs increased with increasing initial population (propagule) size and length of establishment time. Areas along the Mississippi, Ohio, and lower portions of the Missouri river drainages had the highest probability of wild pig establishment with many regions having probabilities close to 1. Spread rates demonstrated strong spatial heterogeneity with the greatest rates of spread (5.8 watersheds/year) occurring from 2008 to 2013 prior to the establishment of a National wild pig control program in 2013. Spread rates declined 82% (0.57 watersheds/year) in the period from 2013 to 2021 compared to the period from 1982 to 2013. We found significant positive associations among stochastic population growth rate and observed geographic rates of spread. Stochastic population growth rate explained a large amount of variation (79.3–92.1%) in annual rate of watershed spread of wild pigs. Our predicted probabilities of establishment and population growth can be used to inform surveillance and control efforts to reduce the potential for establishment and spread of wild pigs.

Stock Trend Prediction Using KNN Algorithm

Stock forecasting has always been a difficult task for statisticians and financial analysts. The key strategy used to make this prediction is buying stocks with a high probability of price growth and selling stocks with a high probability of price decline. There are typically two approaches to stock market forecasting. One of them is fundamental analysis, which is dependent on a company's methodology and fundamental data. The performance of the supervised machine learning algorithm KNN (K-Nearest Neighbor) is evaluated by the author in this study. Stock trading is one of the most significant activities in the world of finance. Trying to anticipate the future value of a stock or other financial instrument traded on a financial exchange is known as stock market prediction. Python is the computer language used to make stock market predictions using machine learning. In this article, we present a Machine Learning (ML) approach that will be trained using the stock market data that is currently accessible, gain intelligence, and then use the learned information to make an accurate prediction. This study employs prices with both daily and up-to-the-minute frequencies and a machine learning method known as K-Nearest Neighbor to forecast stock prices for both large and small capitalizations and in the three separate marketplaces.

Incorporating human dimensions is associated with better wildlife translocation outcomes

Wildlife translocations are increasingly used to combat declining biodiversity worldwide. Successful translocation often hinges on coexistence between humans and wildlife, yet not all translocation efforts explicitly include human dimensions (e.g., economic incentives, education programs, and conflict reduction assistance). To evaluate the prevalence and associated outcomes of including human dimensions as objectives when planning translocations, we analyze 305 case studies from the IUCN’s Global Re-Introduction Perspectives Series. We find that fewer than half of all projects included human dimension objectives (42%), but that projects including human dimension objectives were associated with improved wildlife population outcomes (i.e., higher probability of survival, reproduction, or population growth). Translocation efforts were more likely to include human dimension objectives if they involved mammals, species with a history of local human conflict, and local stakeholders. Our findings underscore the importance of incorporating objectives related to human dimensions in translocation planning efforts to improve conservation success.

Investigation on Effective Thermal Conductivity of Fibrous Porous Materials as Vacuum Insulation Panels’ Core Using Lattice Boltzmann Method

Vacuum Insulation Panels (VIPs) provide significant adiabatic performance for heat/cooling systems to reduce energy consumption. The application of fibrous porous material (FPM) as the ideal core of VIPs has gained global attention in recent decades. The microstructure and physical properties of FPMs, filled as novel VIPs’ core material, and holding superior thermal performance, affected effective thermal conductivity (ETC) greatly. Aiming to deeply understand heat transfer mechanisms, a holistic simulation method that combined with a developed 3D FPM structure generation method and a D3Q15-Lattice Boltzmann method (LBM) is proposed to simulate the heat transfer in FPM and to illuminate the influence factors of ETC on the microstructure of FPM in a vacuum. The improved and modified mesoscopic 3D fibrous random micro-structure generation approach involved five structural parameters: generation probability of nucleus growth, fiber length, diameter, coincidence rate, and orientation angle. The calculation model of ETC is established, and the discrete velocity, distribution, evolution, and boundary conditions of D3Q15-LBM are invested in detail. The model is validated with influences of different microstructure parameters. It indicated that FPM with finer diameter, smaller average pore size, and bigger orientation angle easily gain the lower ETC in a vacuum. The ETC was also affected by the orientation angles of fibers. The more the heat transfer direction is inconsistent with the length direction of the fiber, the better the adiabatic performance is. The reliability of the model is verified by comparison, and this work is a reference to optimize the fibrous core of VIPs.

Dynamics of Macroeconomic Uncertainty on Economic Growth in the Presence of Fiscal Consolidation in South Africa from 1994 to 2022

This paper investigates the effects of macroeconomic uncertainty on economic growth in the presence of fiscal consolidation in South Africa. Markov-switching dynamic regression (MSDR) and time-varying parameter vector autoregression (TVP-VAR) were performed using time series data from 1994 to 2022. Less attention has been given directly to the investigation of macroeconomic uncertainty in different regimes of economic growth in South Africa. Three states are found for economic growth, with mean growth rates of negative 6.29% and positive 3.90% and 1.47%, respectively. Macroeconomic uncertainty was found to have a negative impact of 6.72%, 4.38%, and 3.08% in states 1 to 3, respectively. Fiscal consolidation provided an accommodative policy, as it reduced the negative impact of macroeconomic uncertainty by 3.17%, 1.80%, and 0.92% in states 1 to 3, respectively. However, fiscal consolidation does not completely reduce the negative impact of macroeconomic uncertainty. The transition probabilities of economic growth moving and returning to the same states are 29.46%, 34.07%, and 58.02%, in each state, respectively. The time-varying impulse response functions showed that the shock of macroeconomic uncertainty harms economic growth. Nevertheless, the multiplier effect is not large; however, the economy operates below equilibrium and does not restore equilibrium after the effect of macroeconomic uncertainty. This reflects that it takes time for macroeconomic uncertainty to filter out of the South African economy. It is recommended that fiscal consolidation be considered as an accommodative fiscal policy to reduce macroeconomic uncertainty but not as a main policy for economic growth.

Ruthenium-cobalt single atom alloy for CO photo-hydrogenation to liquid fuels at ambient pressures

Photothermal Fischer-Tropsch synthesis represents a promising strategy for converting carbon monoxide into value-added chemicals. High pressures (2-5 MPa) are typically required for efficient C-C coupling reactions and the production of C5+ liquid fuels. Herein, we report a ruthenium-cobalt single atom alloy (Ru1Co-SAA) catalyst derived from a layered-double-hydroxide nanosheet precursor. Under UV-Vis irradiation (1.80 W cm−2), Ru1Co-SAA heats to 200 °C and photo-hydrogenates CO to C5+ liquid fuels at ambient pressures (0.1-0.5 MPa). Single atom Ru sites dramatically enhance the dissociative adsorption of CO, whilst promoting C-C coupling reactions and suppressing over-hydrogenation of CHx* intermediates, resulting in a CO photo-hydrogenation turnover frequency of 0.114 s−1 with 75.8% C5+ selectivity. Owing to the local Ru-Co coordination, highly unsaturated intermediates are generated during C-C coupling reactions, thereby improving the probability of carbon chain growth into C5+ liquid fuels. The findings open new vistas towards C5+ liquid fuels under sunlight at mild pressures.

Abstract 5108: Overcoming roadblocks of immunotherapy in non-small cell lung cancer

Abstract Non-small cell lung cancer (NSCLC) is one of the major causes of cancer-related death worldwide. Immunotherapy has helped to increase the survival of NSCLC patients, but the therapeutic response is limited to 23-26% of patients. While many factors impact immunotherapy failure, we have focused on a few, (a) heterogeneous expression of immune checkpoints (ICs) limiting the use of single immune checkpoint inhibitor (ICI) for everyone, (b) additional ICs responsible for blocking innate immune system and lack of antigen presentation to the T cells, and (c) lack of rationally designed combination therapies.Commonly used immunotherapies for NSCLC block PD1-PDL1 interaction, but the majority of the NSCLC patient does not have high PDL1 expression indicating PD1-PDL1 as a subsidiary mode of immune evasion. So, it is necessary to include additional ICIs in order to achieve adequate objective response in all NSCLC patients. In order to investigate the immune checkpoint expression, we screened several NSCLC patient-derived tumor tissues, and only 33% of them showed high expression of PDL1, whereas 64.6% of patients had high CD47 expression. CD47, an innate immune regulator, is overexpressed in lung cancer cells and delivers an “eat-me-not” signal by binding to signal regulatory protein alpha (SIRPα) in macrophage resulting in diminishing phagocytosis and antigen presentation to the T cells.Combining anticancer drugs with immunotherapy agents has become a popular approach to achieve a less toxic and long-acting objective therapeutic response. Here, we introduce antibody conjugated drug loaded nanotherapeutics (ADNs) consisting of a targeted therapy drug, phosphatidylinositol 3-kinase (PI3K) inhibitor PI103, and decorated with two ICIs for CD47 and PDL1. The ADN particles have been designed based on classical liposomal supramolecular nanoparticles followed by surface functionalization by the specific antibody. The anti-CD47-PDL1-ADN has shown increased cellular internalization and delivery of PI103 than IgG-ADN and anti-PDL1-ADN. The anti-CD47-PDL1-ADN showed low hematotoxicity and higher cell-killing potency for the cancer cells. The bispecific anti-CD47-PDL1-ADNs can block PD1-PDL1 and SIRPα-CD47 immune checkpoint interaction, activating both the innate (macrophage) and adaptive (T cells) immune responses. Reduced tumor growth and higher survival probability have been observed in the syngeneic LLC tumor model for anti-CD47-PDL1-ADN than monotherapy and traditional immunotherapy.In summary, we have introduced a lung cancer treatment strategy that can be an effective therapy for NSCLC patients, irrespective of the PDL1 expression level. The strategy combining bispecific immunotherapy and targeted therapy for activating the innate and adaptive immune systems and delivering targeted therapy drugs can emerge as a significant advance in the treatment of NSCLC patients. Citation Format: Tanmoy Saha, Shiladitya Sengupta. Overcoming roadblocks of immunotherapy in non-small cell lung cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5108.

CO2 Hydrogenation: Na Doping Promotes CO and Hydrocarbon Formation over Ru/m-ZrO2 at Elevated Pressures in Gas Phase Media.

Sodium-promoted monoclinic zirconia supported ruthenium catalysts were tested for CO2 hydrogenation at 20 bar and a H2:CO2 ratio of 3:1. Although increasing sodium promotion, from 2.5% to 5% by weight, slightly decreased CO2 conversion (14% to 10%), it doubled the selectivity to both CO (~36% to ~71%) and chain growth products (~4% to ~8%) remarkably and reduced the methane selectivity by two-thirds (~60% to ~21%). For CO2 hydrogenation during in situ DRIFTS under atmospheric pressure, it was revealed that Na increases the catalyst basicity and suppresses the reactivity of Ru sites. Higher basicity facilitates CO2 adsorption, weakens the C-H bond of the formate intermediate promoting CO formation, and inhibits methanation occurring on ruthenium nanoparticle surfaces. The suppression of excessive hydrogenation increases the chain growth probability. Decelerated reduction during H2-TPR/TPR-MS and H2-TPR-EXAFS/XANES at the K-edge of ruthenium indicates that sodium is in contact with ruthenium. A comparison of the XANES spectra of unpromoted and Na-promoted catalysts after H2 reduction showed no evidence of a promoting effect involving electron charge transfer.

Decoupling between carbon source and sink induced by responses of daily stem growth to water availability in subtropical urban forests

Urban forests are anticipated to offer sustainable ecosystem services, necessitating a comprehensive understanding of the ways in which trees respond to environmental changes. This study monitored stem radius fluctuations in Cinnamomum camphora and Taxodium distichum var. imbricatum trees using high-resolution dendrometers at two sites, respectively. Gross primary production (GPP) was measured using eddy-covariance techniques and aggregated to daily sums. Hourly and daily stem radius fluctuations were estimated across both species, and the responses of stems to radiation (Rg), air temperature (Tair), vapor pressure deficit (VPD), and soil humidity (SoilH) were quantified using Bayesian linear models. The diel growth patterns of the monitored trees showed similar characteristics at the species level. Results revealed that trees growth occurred primarily at night, with the lowest hourly contribution to total growth and probability for growth occurring in the afternoon. Furthermore, the Bayesian models indicated that VPD was the most important driver of daily growth and growth probability. After considering the potential constraints imposed by VPD, a modified Gompertz equation showed good performance, with R2 ranging from 0.94 to 0.99 for the relationship between accumulative growth and time. Bayes-based model-independent data assimilation using advanced Markov chain Monte Carlo (MCMC) algorithms provided deeper insights into nonlinear model parameterization. Finally, the quantified relationship between GPP and stem daily growth revealed that the decoupling between carbon source and sink increased with VPD. These findings provided direct empirical evidence for VPD as a key driver of daily growth patterns and raise questions about carbon neutrality accounting under future climate change given the uncertainties induced by increased water stress limitations on carbon utilization.

Identifying the Performance Descriptor in Direct Syngas Conversion to Long-Chain α-Olefins over Ruthenium-Based Catalysts Promoted by Alkali Metals

Fischer-Tropsch synthesis (FTS) provides a nonpetroleum route for the production of value-added α-olefins from syngas. However, regulating the product distribution to promote the formation of long-chain α-olefins while maintaining low selectivity to C1 byproducts (CO2 and CH4) remains a great challenge. Herein, a series of alkali metal-promoted Ru/SiO2 catalysts were synthesized to investigate the effect of alkali metals and identify the performance descriptor for syngas to α-olefins. X-ray absorption and photoelectron spectroscopy as well as CO diffuse reflectance infrared Fourier transformation spectra revealed that Ru’s electronic structure can be tuned by the addition of alkali metal promoters. The Allen scale electronegativity deviation between the metallic Ru and the alkali metal promoter, which was identified as a performance descriptor, was correlated with the initial turnover frequency (TOF) and olefins distribution, as well as the chain growth probability. In addition, the fraction of olefin products was successfully adjusted from lower olefins (50.3%) to long-chain α-olefins (85.8%) by controlling the kinds of alkali metal promoters. Evidences from X-ray absorption spectroscopy and chemisorption characterizations revealed that the controllable Ru electron density could enhance CO adsorption and hinder the reactivity of chemisorbed H species, thus benefiting the α-olefin production. These results offer a comprehensive view of the electronic effect for regulating product selectivity during the Fischer-Tropsch reaction process.

Technological and Organizational Change and the Careers of Workers

Abstract This paper investigates the effects of technological and organizational change (T&O) on jobs and workers. We show that although T&O reduces firm demand for routine relative to abstract task-based jobs, affected workers do not face higher probability of non-employment or lower earnings growth than unaffected workers. Rather, firms that adopt T&O offer routine workers retraining opportunities to upgrade to more abstract jobs. Older workers form an important exception: T&O increases the risk that they permanently withdraw from the labor market and reduces their earnings, regardless of the tasks they performed in the firm prior to T&O.

CAR-T Cells with Phytohemagglutinin (PHA) Provide Anti-Cancer Capacity with Better Proliferation, Rejuvenated Effector Memory, and Reduced Exhausted T Cell Frequencies.

The development of genetic modification techniques has led to a new era in cancer treatments that have been limited to conventional treatments such as chemotherapy. intensive efforts are being performed to develop cancer-targeted therapies to avoid the elimination of non-cancerous cells. One of the most promising approaches is genetically modified CAR-T cell therapy. The high central memory T cell (Tcm) and stem cell-like memory T cell (Tscm) ratios in the CAR-T cell population increase the effectiveness of immunotherapy. Therefore, it is important to increase the populations of CAR-expressing Tcm and Tscm cells to ensure that CAR-T cells remain long-term and have cytotoxic (anti-tumor) efficacy. In this study, we aimed to improve CAR-T cell therapy's time-dependent efficacy and stability, increasing the survival time and reducing the probability of cancer cell growth. To increase the sub-population of Tcm and Tscm in CAR-T cells, we investigated the production of a long-term stable and efficient cytotoxic CAR-T cell by modifications in the cell activation-dependent production using Phytohemagglutinin (PHA). PHA, a lectin that binds to the membranes of T cells and increases metabolic activity and cell division, is studied to increase the Tcm and Tscm population. Although it is known that PHA significantly increases Tcm cells, B-lymphocyte antigen CD19-specific CAR-T cell expansion, its anti-cancer and memory capacity has not yet been tested compared with aCD3/aCD28-amplified CAR-T cells. Two different types of CARs (aCD19 scFv CD8-(CD28 or 4-1BB)-CD3z-EGFRt)-expressing T cells were generated and their immunogenic phenotype, exhausted phenotype, Tcm-Tscm populations, and cytotoxic activities were determined in this study. The proportion of T cell memory phenotype in the CAR-T cell populations generated by PHA was observed to be higher than that of aCD3/aCD28-amplified CAR-T cells with similar and higher proliferation capacity. Here, we show that PHA provides long-term and efficient CAR-T cell production, suggesting a potential alternative to aCD3/aCD28-amplified CAR-T cells.

A contemporary look at the accuracy of the ‘double pulse technique’ for measuring rates of crystal nucleation; molecular-kinetic and non-classical mechanisms of initial growth of the just-born crystals

Microscopically visible crystals are indispensable for measuring nucleation rates by means of the ‘double pulse technique’ (DPT). Therefore, the accuracy of the DPT depends on the survivability of the just-born crystals during their initial growth and (possible) dissolution. First, because the critical nuclei stay in a labile equilibrium with the mother phase (meaning equal growth and dissolution probabilities), half of the critical nuclei must be dissolved. Second, because of interphase fluctuations and crystal coalescence, the number densities of super-critically sized nuclei can also be decreased. To estimate the survivability of super-critical crystals, the probabilities for attachment/detachment of molecules to/from such crystals are considered in full detail from a molecular-kinetic point of view. It is shown that the probability of decomposition down to subcritical dimension, which is of importance for the accuracy of the DPT, is negligibly small already for crystals by only three molecules larger than the critical size. Besides, except for extremely high supersaturations, also the oriented attachment of nanocrystals is of little consequence for the accuracy of the DPT. The conclusion is that, because the nucleation of crystals is a stochastic process, the nucleation rates measured by means of the DPT are dependable.