The effects of firm ownership and affiliation on government’s target setting on energy conservation in China

Targets of energy conservation in China are allocated by the central government across subnational jurisdictions and firms. However, we know little about why some regulated entities receive higher mandates than others. In this paper, we use the Top- 1,000 Enterprises Energy-Saving Program, which was adopted in 2006, to examine the underlying mechanisms through which energy-saving targets are assigned. After considering a variety of control variables, we find that state-owned enterprises (SOEs) receive significantly higher targets than non-SOE firms. In addition, centrally affiliated firms are assigned with higher targets than their locally affiliated counterparts. Furthermore, firm ownership and affiliation interactively affect target assignment, with central non-SOE firms bearing the heaviest tasks. We then derive theoretical and policy implications from the findings for energy policy and resultsbased management strategy

The effects of firm ownership and affiliation on government’s target setting on energy conservation in China

Targets of energy conservation in China are allocated by the central government across subnational jurisdictions and firms. However, we know little about why some regulated entities receive higher mandates than others. In this paper, we use the Top- 1,000 Enterprises Energy-Saving Program, which was adopted in 2006, to examine the underlying mechanisms through which energy-saving targets are assigned. After considering a variety of control variables, we find that state-owned enterprises (SOEs) receive significantly higher targets than non-SOE firms. In addition, centrally affiliated firms are assigned with higher targets than their locally affiliated counterparts. Furthermore, firm ownership and affiliation interactively affect target assignment, with central non-SOE firms bearing the heaviest tasks. We then derive theoretical and policy implications from the findings for energy policy and resultsbased management strategy

The Temperature Dependence of Salt−Protein Association Is Sequence Specific^†

Molecular dynamics (MD) simulations are used to probe the origin of the unexpected temperature dependence of salt accumulation in the C-terminal region of the protein human lymphotactin. As in previous MD simulations, sodium ions accumulate in an enhanced manner near the C-terminal helix at the lower temperature, while the temperature dependence of chloride accumulation is much weaker and slightly positive. In a designed mutant in which all positively charged residues in the C-terminal helix are replaced with neutral polar groups (Ser), the unexpected temperature dependence of the sodium ions is no longer observed. Therefore, these simulations convincingly verified the previous hypothesis that the temperature dependence of ion−protein association is sensitive to the local sequence. This is explained qualitatively in terms of the entropy of association between charged species in solution. These findings have general implications for the interpretation of thermodynamic quantities associated with binding events where ion release is important, such as protein−DNA interactions

Activation Mechanism of a Signaling Protein at Atomic Resolution from Advanced Computations

Advanced computational techniques including transition path sampling and free energy calculations are combined synergistically to reveal the activation mechanism at unprecedented resolution for a small signaling protein, chemotaxis protein Y. In the conventional “Y−T coupling” model for response regulators, phosphorylation induces the displacement of the conserved Thr87 residue through hydrogen-bond formation, which in turn makes it sterically possible for Tyr106 to isomerize from a solvent exposed configuration to a buried rotameric state. More than 160 unbiased activation trajectories show, however, that the rotation of Tyr106 does not rely on the displacement of Thr87 per se. Free energy calculations reveal that the Tyr106 rotation is a low-barrier process in the absence of the Thr87-phosphate hydrogen bond, although the rotation is stabilized by the formation of this interaction. The simulations also find that structural change in the β4−α4 loop does not gate the Tyr106 rotation as suggested previously; rather, the rotation of Tyr106 stabilizes the activated configuration of this loop. The computational strategy used and mechanistic insights obtained have an impact on the study of signaling proteins and allosteric systems in general

sj-docx-1-rop-10.1177_0734371X221141988 – Supplemental material for Does Employee Pay Variation Increase Government Performance? Evidence From a Cross-National Analysis

Supplemental material, sj-docx-1-rop-10.1177_0734371X221141988 for Does Employee Pay Variation Increase Government Performance? Evidence From a Cross-National Analysis by Xu Han, Liang Ma and James Perry in Review of Public Personnel Administration</p

DataSheet1_DecOT: Bulk Deconvolution With Optimal Transport Loss Using a Single-Cell Reference.docx

Tissues are constituted of heterogeneous cell types. Although single-cell RNA sequencing has paved the way to a deeper understanding of organismal cellular composition, the high cost and technical noise have prevented its wide application. As an alternative, computational deconvolution of bulk tissues can be a cost-effective solution. In this study, we propose DecOT, a deconvolution method that uses the Wasserstein distance as a loss and applies scRNA-seq data as references to characterize the cell type composition from bulk tissue RNA-seq data. The Wasserstein loss in DecOT is able to utilize additional information from gene space. DecOT also applies an ensemble framework to integrate deconvolution results from multiple individuals’ references to mitigate the individual/batch effect. By benchmarking DecOT with four recently proposed square loss-based methods on pseudo-bulk data from four different single-cell data sets and real pancreatic islet bulk samples, we show that DecOT outperforms other methods and the ensemble framework is robust to the choice of references.</p

Event-related driver stress detection with smartphones among young novice drivers

Complex and diverse driving situations can pose short-term stressors to novice drivers. Continuously detecting stress is essential for driver training, stress intervention, and the design of in-vehicle information systems. This study designed and validated a driver stress detection method at the event level based on machine learning algorithms and facial features captured with smartphones. Thirty young novice drivers completed two driving tasks containing eight events of two versions (neutral and stressful), with psychological, physiological, and facial data collected. Four combinations of input data types and six machine learning algorithms were used to detect stressful events. The KNN algorithm with facial plus individual profile features yielded the highest accuracy of 89.2%. Adding individual profile features can improve classification performance. Facial areas such as brow, eye, jaw, nose, and mouth were most sensitive to stress. This approach could provide more temporal-spatial information about the driver’s stress levels during the whole driving process. Practitioner Summary: This paper proposed a method to detect driver stress at the event level with smartphones. Models with facial plus individual profile features and the KNN algorithm had the most outstanding classification performance. The presented approach can serve as a tool for improving in-vehicle interaction system design when considering driver stress. Abbreviations: GSR: galvanic skin response; ECG: electrocardiography; HR: heart rate; HRV: heart rate variability; RGB: red green blue; NIR: near-infrared; IP: individual profile; DSI: driver stress inventory; APS: arousal predisposition scale; API: application programming interface; PPG: photoplethysmography; EDR: electrodermal response; PD: pupil diameter; SCL: skin conductance level; RF: random forest; KNN: k-nearest neighbour; LDA: linear discriminant analysis; QDA: quadratic discriminant analysis; SVML: support vector machines with the linear kernel; SVMP: support vector machines with the polynomial kernel; TP: true positive; TN: true negative; FP: false positive; FN: false negative; t-SNE: t-distributed stochastic neighbour embedding</p

Effects of Temperature and Salt Concentration on the Structural Stability of Human Lymphotactin: Insights from Molecular Simulations

Extensive molecular dynamics (MD) simulations (∼70 ns total) with explicit solvent molecules and salt ions are carried out to probe the effects of temperature and salt concentration on the structural stability of the human Lymphotactin (hLtn). The distribution of ions near the protein surface and the stability of various structural motifs are observed to exhibit interesting dependence on the local sequence and structure. Whereas chloride association to the protein is overall enhanced as the temperature increases, the sodium distribution in the C-terminal helical region and, to a smaller degree, the chloride distribution in the same region are found higher at the lower temperature. The similar trend is also observed in nonlinear Poisson−Boltzmann calculations with a temperature-dependent water dielectric constant, once conformational averaging over a series of MD snapshots is done. The unexpected temperature dependence in the ion distribution is explained on the basis of the cancellation of association entropy for ion−side chain pairs of opposite-charge and like-charge characters, which have positive and negative contributions, respectively. The C-terminal helix is observed to partially melt whereas a short β strand forms at the higher temperature with little salt dependence. The N-termal region, by contrast, develops partial helical structure at a higher salt concentration. These observed behaviors are consistent with solvent and salt screening playing an important role in stabilizing the canonical chemokine fold of hLtn