Post Data Analysis Research Articles

Practical Applications of Grand-canonical Electronic Structure Calculations in Electrochemical Simulation.

Modeling electrified interfaces has long been a great challenge in electrochemistry. In recent years, the grand-canonical treatment for electrons has gradually been developed, and its combination with density functional theory has been widely used to simulate electrochemical processes on an atomistic scale. In this Perspective, we aim to discuss several practical applications of this powerful technique after a short review of necessary fundamentals. We will begin with capacitor-based parametrization method of grand-canonical calculated results. If considering the electrodes under different applied potentials as different materials, the parametrization can be viewed as a kind of "quadratic scaling relation", which might reduce the overall computational costs by data postanalysis rather than algorithm development. Following an example of the abnormal potential-independent energetic curve within the bandgap area, we turn the topic to the semiconducting electrodes. Meanwhile, the specific behaviors of the bandgap also indicate that besides the reaction thermodynamics and kinetics, the detailed electronic structure of the system can also be well described by the grand-canonical treatment on electrons. Several possibilities for further applications are proposed correspondingly and summarized at the end of paper. We believe that the grand-canonical treatment for electronic structure calculations can greatly enrich our understanding of the fundamental mechanisms under electrochemical environments.

Evaluation of the outcomes of equity-deserving individuals receiving services and support from integrated substance use health and mental health services: a pilot study protocol

BackgroundGiven the close relationship that can exist between substance use health and mental health (SUHMH) concerns, the need for more integrated services and support has been identified. However, research on the effective integration of SUHMH services and their impact on outcomes of individuals accessing them remains limited. In particular, the unique outcomes of individuals facing significant structural inequities in the health care system, i.e., Indigenous Peoples in Canada, including First Nations, Inuit and Métis (FNIM), and equity-deserving (ED) groups, have not been evaluated while receiving integrated SUHMH services. This paper describes the protocol for a pilot research project, which will evaluate the change in clinical and social outcomes of individuals receiving integrated SUHMH services in relation to their intersectionality status, a linear score ranging from identifying with no FNIM and ED groups to identifying with one or multiple groups.MethodsThis study recruits 100 individuals who receive SUHMH services and support from a community health center in Ottawa, Canada and assessed their FNIM and ED status and clinical and social outcomes at baseline and three-month follow-up. At the time of writing this manuscript, the baseline data collection was completed. Follow up assessment occurs three months after baseline data was collected. A smaller group of these participants will be purposefully selected match the proportion of FNIM and ED groups from the two-time assessment. They will be invited to participate in a post-data analysis validation consultation session to ensure that the findings are reflective of the experiences of individuals receiving SUHMH services, alternative interpretations are brought forward, and implications are driven by those who will be most impacted. This consultation may also inform knowledge mobilization activities and future studies. This study also recruited staff in different roles from the providing center to rate the implementation of key dimensions of equity-oriented care into their practices and their level and capability to provide integrated services and support to individuals with cooccurring substance use disorders and mental illnesses.DiscussionThe results of this study will inform integrated SUHMH services by emphasizing equity and inclusive approaches, and engagement with the community. Substance use health; Mental health; Integrated services and support; Equity-deserving populations; Equity-oriented care.

Polar coordinate-based background removal algorithm for 2D x-ray scattering data.

During the data collection of x-ray diffraction experiments with various detectors, background signals are often unavoidable along with the sample signal. Addressing the background during post-data analysis is not a straightforward task. In this work, we introduced an algorithm specifically designed to handle centrally symmetric two-dimensional x-ray diffraction data and processed the data using the Python programming language. The two-dimensional data are first transformed from Cartesian coordinates to polar coordinates. Second, utilizing existing background processing algorithms, one-dimensional background curves are identified for each azimuth angle. These background data are then merged to generate two-dimensional background data. Finally, by subtracting the background from the original data, we obtain the clear diffraction signal. The algorithm can effectively remove the background from x-ray diffraction data and exhibits the ability to handle backgrounds with high intensity and irregular shapes, and the discernibility of the weak signal is significantly enhanced. Moreover, researchers have the flexibility to choose whether to preserve or eliminate the signals from additional amorphous components based on their needs. This algorithm will provide researchers with the possibility for further data analysis.

Real-time measurement of electron temperature using a coupled centre-tapped emissive probe and a Langmuir probe (CCTELP)

Abstract Conventional electrostatic probes are commonly used for measuring the plasma parameters like plasma density, electron temperature, plasma potential and floating potential respectively in a laboratory plasma to unveil physical processes of relevance to magnetosphere and fusion plasmas. With such probes, real-time measurement of electron temperature and its fluctuating AC component becomes very difficult. These measurements are significant as they directly give the measure of energy flux and hence can be utilized in estimating the turbulence-induced energy loss in any plasma system, especially useful for electron temperature gradient plasmas. Although Triple Langmuir Probe (TLP) diagnostics provide information on real-time measurement of electron temperature, this involves many complications. These complications of TLP are suitably overcome by the proposed diagnostic, which makes use of a combination of a closely separated centre tap emissive probe (CTEP) and Langmuir probe (LP) installed on a single probe head. The coupled centre-tapped emissive and Langmuir probe (CCTELP) provides direct measurement of electron temperature (T_e) and its fluctuations (T ̃_e). The design of the proposed diagnostic is very simple and it is almost free of rigorous control electronics and post-data analysis otherwise needed to estimate the electron temperature. These features make this diagnostic an additional and simple candidate for real-time measurement of electron temperature and its fluctuation. The paper will highlight details on this novel diagnostics, called CCTELP for the measurement in Maxwellian plasmas.

Study Of Energy Management And Efficiency In Industrial Processes: Analysis Of Implementation And Its Impact On Productivity

This study focuses on the implementation and analysis of energy management and efficiency in the context of industrial processes to enhance productivity. Drawing upon literature review on the fundamental concepts of energy management and best practices in industries, this research identifies strategies and methods that can be applied to optimize energy use in manufacturing environments. The research methodology involves gathering data from various sources to evaluate the practical implementation of energy management strategies in manufacturing industries, including pre- and post implementation data analysis. The findings provide deep insights into the effectiveness of specific measures in reducing energy consumption, improving operational efficiency, and their overall impact on productivity. The study also highlights challenges that may arise in implementing energy management strategies, such as initial costs, staff training needs, and technology integration. However, the long-term benefits of efficient energy management include reduced operational costs and environmental sustainability. By combining technical and managerial approaches, this research provides a foundation for better decision-making in adopting sustainable practices in the industrial sector.

Psycho-social predictors of motivation for treatment in patients with mental disorders: the role of adverse childhood experiences and internalized stigma.

IntroductionMotivation for treatment is an important socio-psychological characteristic of patients, which is subject to the joint influence of various factors, each of which may require specific rehabilitation interventions.ObjectivesTo analyze and evaluate the cumulative influence of adverse childhood experiences (ACE), internal stigma, social characteristics on the intensity of treatment motivation in patients with mental disorders.Methods 102 patients with mental disorders were examined using Adverse Childhood Experience Questionnaire (ACEQ), Russian-language validated Internalized Stigma of Mental Illness (ISMI) scale and Treatment Motivation Assessment Questionnaire (TMAQ).Results As a result of regression analysis (table 1), a model was obtained that predicted an increase in the chances of high patient’s motivation for treatment with an increase in the total score of ACEs (ACEQ total score) and with higher education. The overall severity of internal stigma (ISMI total score) did not show a significant effect on the chances of developing intense motivation in patients. Table 1.Model of logistic regression analysis of educational, ACE total score and ISMI total score with the severity of motivation for treatment.PredictorBSEpExp (B)95% confidence interval for EXP(B)Secondary education1,1200,6990,1093,0650,778-12,074Higher education1,9720,775,0117,1891,574-32,834ISMI total score-0,4350,7730,5740,6470,142-2,946ACEQ total score0,3460,1470,0191,4141,060-1,886After post data analysis (table 2), a cut-off point was established for the ACEQ total score of 4 points, corresponding to an increased chances of high patient’s treatment motivation. Table 2.Results of the test ROC analysis for ACEQ total score and the severity of motivation for treatment.CutpointSensitivity (%)Specificity (%)Youden’s indexAUC364.71%53.57%0.1830.689450%75%0.2500.689538.24%85.71%0.2390.689ConclusionsACEs may likely be a source of posttraumatic growth in adulthood in patients with mental illness specially if their count amounts to 4 or more variants. The role of social and psychological characteristics of patients with mental disorders in the psychology of the treatment process should be considered systemically, rather than discretely.Disclosure of InterestNone Declared

Energetic and dynamic characterization of pollutant dispersion in varied building layouts through an augmented analysis procedure

This work presents a post-data analysis procedure, namely, proper orthogonal decomposition (POD)–dynamic mode decomposition (DMD)–discrete Fourier transform analysis, for evaluating the dominant features of the flow fields from both energetic and dynamic perspectives. The large-eddy simulation (LES) was first employed to reproduce the flow field surrounding three types of building layouts. Subsequently, both POD and DMD were conducted according to LES simulation results. The extracted modes were classified into three types based on the POD and DMD: Type-1 mode: energetically and dynamically significant mode, Type-2 mode: energetically significant and dynamically insignificant mode, and Type-3 mode: energetically insignificant and dynamically significant mode. The findings indicate that Type-1 mode governs the primary velocity field and the predominant vortex patterns observed at the rear of the building arrays, as the reduction of inter-building widths leads to a shorter flow separation region. Type-2 mode is characterized by the presence of small-scale vortices and the high turbulent kinetic energy region, which periodically triggers pollutant increase in the vicinity of structures. Type-3 mode demonstrates a minimal energetic influence on the flow field; nevertheless, it significantly contributes to the consistent build-up of pollutants within the far-wake region. The present study also investigates the predominant coherent structures of flow fields concerning various building layouts and highlights the influence of passage widths on the efficiency of pollutant removal. This comprehensive analysis enables a systematic exploration of flow patterns within various building layouts, offering potential solutions for pollutant dispersion challenges in metropolitan areas.

PERFORMANCE EVALUATION OF HEXACOPTER UAV (ANGRAU- PUSHPAK) SPRAYING FOR MANAGEMENT OF CHILLI THRIPS (Thrips parvispinus)

The study aimed at evaluating efficacy of UAV spraying in managing invasive thrips, Thrips parvispinus on chilli. The experiment was conducted at operational research project (ORP) site at Lam village of Guntur district during kharif 2022-23 with restricted randomized block design. The recommended doses of pesticides issued by Central Insecticide Board and Registration Committee(CIB&RC), GoI, New Delhi were adapted. The treatments imposed were of 100%, 75% and 50% RDP with UAV and 100% RDP with human backpack sprayer and a control plot with only water spraying with drone for asserting the efficacy of drone spraying when sprayed at low volume spraying (25 L ha-1).The first spray to control thrips was carried out 112 DAS (Days After Sowing) with a spinetoram 11.7% SC on with analysis of pre and post spraying (5 days after spraying) results showed that the bio-efficacy when sprayed with 100% RDP (T1), 75% RDP(T2), 50% RDP (T3) with drone and 100% RDP with human back pack sprayer (T4) and control(T5)reduced number of thrips per flower from 7.57 to 5.8, 7.55 to 6.40, 7.55 to 10.22, 8.05 to 8.22, 8.05 to 12.95, respectively with a percent reduction over control of 50.75, 46.19, 23.65 and 36.57, respectively. The second spray was carried out at 119 DAS with Flubendiamide 19.92% +Thiacloprid 19.92% SC. The pre and post spraying (5 days after spraying) data analysis revealed that the reduction of thrips per flower over control in T1, T2, T3, T4 and T5 to 7.37, 8.32, 12.12, 10.25 and 16.03 and the percent reduction over control in T1, T2, T3 and T4 are 52.22%, 44.88%, 24.29% and 36.78%, respectively. The third spray with Fipronil 80% WG was carried out at 126 DAS and the pre and post spraying data analysis revealed that the number of thrips per flower are 5.27, 6.47, 10.55, 8.05 and 16.83 with a percent reduction over control of 68.83, 62.34, 22.08 and 38.96, respectively. The fourth spray was carried out at 133 DAS with spirotetramat 25.31% w/w OD and the pre and post spray data analysis revealed that the number of thrips per flower are of 5.12, 5.75, 9.5, 8.5 and 18.22 in T1, T2, T3, T4 and T5 and the percent reduction over control in T1, T2, T3 and T4 are 66.59, 61.68, 40.89 and 46.92, respectively. During the four sprays, it was observed that in all treatments, there was no phytotoxicity due to these chemicals spraying and the NDVI values recorded were 0.77, 0.76, 0.64, 0.72 and 0.34, respectively in the treatments T1, T2, T3, T4 and T5. The yields recorded were found to be 58.6, 55.2, 34.5, 53.8 and 14.1 q ha-1. The incremental cost-benefit ratio (ICBR) was found to be highest (4.46) in 75% RDP spray with drone, when compared to 3.58 in 100% RDP, 2.82 in 50% RDP and 2.98 in 100%RDP with human backpack sprayer respectively. The bio-efficacy of all the chemicals revealed that 100% RDP and 75% RDP sprayed with drone are on par with each other, which offers an opportunity to reduce the dosage by25% if sprayed with drone for the same bio-efficacy with highest ICBR.

Optimized design of an extreme low power datalogger for photovoltaic panels

<span lang="EN-US">The paper focuses on the design and implementation of a low cost and compact data logger prototype using an extreme low power (XLP) and low pin count programmable interface controllers (PIC) microcontroller using its own flash memory for the periodic data acquisition storage, while many other works focus in the Arduino Eco-system. It is planned to pick four important analog measures from the photovoltaic system, and store them directly as 10-bit numerical counts, this yields to faster data acquisition and storage (no time consuming for mathematical computation to convert each numerical count of raw data to meaningful real-world data). Avoiding the use of any kind of display and keypad, and keeping the ratio run time over sleep time as low as possible, has a maximum impact on lowering the power consumption. This prototype can be serially linked to a personal computer (PC) to view the acquisition of measurements in real time, and to retrieve all collected data through a terminal application. The experimental results are stored in comma-separated values (CSV) files to ease post data analysis with any spread sheet software, for statistical calculations and graphs drawing, in order for instance, to find the faults of the photovoltaic system and optimize its management and its performance.</span>

3D to 2D perspectives - Traditional and new doping and metrology challenges at the nanoscale

In this perspectives paper we will explore the doping state-of-the-art as it evolves for 3D to 2D structures and materials, and the following impact on the metrology methods needed to characterise them. Historically, silicon devices for logic complementary metal-oxide-semiconductor (MOS) are built in bulk monocrystalline substrates. In this context bulk silicon substrates are 3D, as there is not the electrostatic confinement associated with more technologically advanced device structures. The determination of technology figures-of-merit such as sheet resistance, impurity concentration and activation profiles versus depth, and reverse bias leakage current to track crystal quality post-doping process, have been the typical methods for evaluation. Since the emergence of FinFET, gate-all-around (GAA) for logic, and layered 2D materials such as transition-metal-dichalcogenides (TMDs) for MOS channel active areas, these figures-of-merit are more awkward to extract, or simply do not apply in the usual sense. Logic devices, like MOS transistors, depend on doping processes to lower access resistance and thus drive performance, traditionally relied on ion implantation to introduce impurities to the substrate, which is a physical bombardment that damages the target material. Gentler doping processes that rely on in-diffusion are an emerging category, and most recently the concept of terminating or functionalising the (near-) surface of the semiconductor is growing in popularity, at least in research labs. Likewise, methods to characterise these require evolution to adapt to the times, from the conventional high-throughput techniques to the more exploratory, albeit lower throughput, methods. Metrology relies upon high-sensitivity, large dynamic range of detection, spatial resolution, as well as time- and cost-efficient sample preparation and post-analysis data interpretation. Driven primarily by the continued development of novel, scaled-down, truly unique device architectures and the introduction of novel materials in the nano-fabrication technology, the portfolio of dopant characterisation methods is unremittingly enlarging its numbers. Herein, we focus our discussion onto dopant profiling for fin and nanowire FETs, and relate these to analysis of test vehicles such as arrays of fin structures with varying dimensions. Although reports detailing correlative use of the dopant characterisation methods are only a few, we present examples that provided unique new information, in absence of which the overall description of the dopant process is inconclusive and, in some cases, misleading.

Deep TMS H1 Coil treatment for depression: Results from a large post marketing data analysis

Phase IV study evaluated Deep TMS for major depression in community settings. Data were aggregated from 1753 patients at 21 sites, who received Deep TMS (high frequency or iTBS) using the H1 coil. Outcome measures varied across subjects and included clinician-based scales (HDRS-21) and self-assessment questionnaires (PHQ-9, BDI-II). 1351 patients were included in the analysis, 202 received iTBS. For participants with data from at least 1 scale, 30 sessions of Deep TMS led to 81.6% response and 65.3% remission rate. 20 sessions led to 73.6% response and 58.1% remission rate. iTBS led to 72.4% response and 69.2% remission. Remission rates were highest when assessed with HDRS (72%). In 84% of responders and 80% of remitters, response and remission was sustained in the subsequent assessment. Median number of sessions (days) for onset of sustained response was 16 (21 days) and for sustained remission 17 (23 days). Higher stimulation intensity was associated with superior clinical outcomes. This study shows that beyond its proven efficacy in RCTs, Deep TMS with the H1 coil is effective for treating depression under naturalistic conditions, and the onset of improvement is usually within 20 sessions. However, initial non-responders and non-remitters benefit from extended treatment.

Multiplexed smFRET Nucleic Acid Sensing Using DNA Nanotweezers

The multiplexed detection of disease biomarkers is part of an ongoing effort toward improving the quality of diagnostic testing, reducing the cost of analysis, and accelerating the treatment processes. Although significant efforts have been made to develop more sensitive and rapid multiplexed screening methods, such as microarrays and electrochemical sensors, their limitations include their intricate sensing designs and semi-quantitative detection capabilities. Alternatively, fluorescence resonance energy transfer (FRET)-based single-molecule counting offers great potential for both the sensitive and quantitative detection of various biomarkers. However, current FRET-based multiplexed sensing typically requires the use of multiple excitation sources and/or FRET pairs, which complicates labeling schemes and the post-analysis of data. We present a nanotweezer (NT)-based sensing strategy that employs a single FRET pair and is capable of detecting multiple targets. Using DNA mimics of miRNA biomarkers specific to triple-negative breast cancer (TNBC), we demonstrated that the developed sensors are sensitive down to the low picomolar range (≤10 pM) and can discriminate between targets with a single-base mismatch. These simple hybridization-based sensors hold great promise for the sensitive detection of a wider spectrum of nucleic acid biomarkers.

Verification and validation by eXtended reality simulations of Test Blanket Modules replacement operations in Air-Fed suits

To study the feasibility of the Test Blanket Modules (TBM) replacement operations in ITER Port Cells, CEA develops a mixed (digital & physical) validation by simulations approach with immersive technology to verify hands-on operations. Main validation criteria concern operator accessibility, posture, detailed procedure sequence and time spent at workstations. Such complex replacement operations will assume series of hands on tasks for both normal and abnormal situations, sometimes with protection such as Air-Fed Suit (AFS). After initial validation of key operation feasibility on digital mock-up, the goal is to optimize the process with minimization of occupational radiation exposure under the As Low As Reasonably Achievable (ALARA) requirement.Virtual reality tools provide relevant means to develop a credible replacement scenario in a context of complex configurations. The process includes features such as ergonomics assessment tool coupled to multi operators’ collaboration, tangible tools and integration of advanced real time physics engine. Lessons learnt from the field of existing CEA facilities enable identifying key parameters related to workstation Humans factors. This first set of observations would help to define methodology and criteria for qualification of operation in AFS.The Digital simulation validation is deployed with a nuclear operator avatar in AFS to demonstrate Nuclear Maintenance Operation feasibility considering study of arduousness, accessibility and visibility thanks to real time motion capture. The recording of the whole simulation allows tracing and replaying for post-analysis data including body angulations, clash detection and operator field of view.The integration of this approach at an early phase of the design process enables validating technical options for replacement scenario. This leads to promising and beneficial results concerning design and integration of complex components in constraint working environments.This paper presents a review of the CEA studies regarding the extended virtual reality capabilities and results to support design TBM integration and replacement scenario within a nuclear environment framework.

Some Features of the Ionospheric Radio Wave Characteristics Over China Observed During the Solar Eclipse of 21 June 2020

AbstractThe Harbin Engineering University, the People's Republic of China, multifrequency multiple‐path coherent radio system operates continuously and provides data for post analysis. The data collected during the solar eclipse of 21 June 2020 have been chosen for this study with the objectives to interpret the variations in the Doppler spectra, Doppler shift, and in the reflected radio wave amplitudes that are associated with the solar eclipse, establish the magnitude and find physical significance of these variations, determine the reduction in the electron density caused by the solar eclipse, and to estimate an increase in wave activity in the ionosphere. The eclipse was accompanied by Doppler spectrum diffuseness resulting from an increase in the number of rays, the temporal variations in the Doppler shift were observed to be bi‐polar, asymmetrical, and anomalously small, with extreme Doppler shift magnitudes varying from −11 to −40 mHz and from 22 to 56 mHz. The duration of processes with negative Doppler shifts varied from 50 to 80 min, and the duration of processes with positive Doppler shifts changed from 30 to 80 min. The multi‐hop propagation (from two to five hops) took place along all propagation paths, with a 360 to 560‐km one‐hop length, due to the anomalous radio wave propagation via the sporadic‐E layer present about 80% of the time on 21 June 2020. The Doppler shift exhibited 4–18‐min period quasi‐sinusoidal variations with 20–10‐mHz amplitudes.

Data reduction through optimized scalar quantization for more compact neural networks

Raw data generation for several existing and planned large physics experiments now exceeds TB/s rates, generating untenable data sets in very little time. Those data often demonstrate high dimensionality while containing limited information. Meanwhile, Machine Learning algorithms are now becoming an essential part of data processing and data analysis. Those algorithms can be used offline for post processing and post data analysis, or they can be used online for real time processing providing ultra low latency experiment monitoring. Both use cases would benefit from data throughput reduction while preserving relevant information: one by reducing the offline storage requirements by several orders of magnitude and the other by allowing ultra fast online inferencing with low complexity Machine Learning models. Moreover, reducing the data source throughput also reduces material cost, power and data management requirements. In this work we demonstrate optimized nonuniform scalar quantization for data source reduction. This data reduction allows lower dimensional representations while preserving the relevant information of the data, thus enabling high accuracy Tiny Machine Learning classifier models for online fast inferences. We demonstrate this approach with an initial proof of concept targeting the CookieBox, an array of electron spectrometers used for angular streaking, that was developed for LCLS-II as an online beam diagnostic tool. We used the Lloyd-Max algorithm with the CookieBox dataset to design an optimized nonuniform scalar quantizer. Optimized quantization lets us reduce input data volume by 69% with no significant impact on inference accuracy. When we tolerate a 2% loss on inference accuracy, we achieved 81% of input data reduction. Finally, the change from a 7-bit to a 3-bit input data quantization reduces our neural network size by 38%.

Can Servant Leadership and Perceived Organisational Support amplify Organisational Commitment among Operational Hotel Employees in Malaysia during the Coronavirus Disease (COVID-19) Pandemic? A Correlation Analysis

The aim of this study called for identifying a correlation, and, if present, the kind of correlation present between the elements of servant leadership, perceived organisational support, and organisational commitment among hotel employees in Malaysia. The underpinning data was based on the opinions of 52 hotel employees selected via stratified random sampling from four operational departments, namely the Front Office, Food and Beverages (F&B), Housekeeping, and Kitchen segments. Post-data analysis subjected to data obtained during the study, servant leadership and perceived organisational support were both found to highly correlate with organisational commitment in facing the Coronavirus disease (COVID-19) outbreak unleased in December 2019. Thus, the output would undeniably contribute to the hotel industry, leaders of said industry, and hotel employees alike in amplifying the level of commitment directed to organisations in the face of a tough situation, such as the COVID–19 pandemic that had occurred worldwide. Accordingly, recommendations for field-adjacent future studies were also furnished to aid the hotel industry in the future.

Effect of Hydrogen Pressure on the Intrinsic Kinetics of Hydrogen Evolution Reaction at Pt(111) Electrode

Many kinetic studies on hydrogen evolution reaction (HER) were done in N2 saturated solutions in order to avoid possible H2 leakage, which results in a variation of H2 concentration at the electrode/electrolyte interface (). It will induce the drift of equilibrium potential (Eeq) and applied activation overpotential (η act) for HER. Consequently, it may result in errors for estimating the kinetic parameters for HER. By taking HER at Pt(111) under RDE configuration as a model reaction, quantitative relation among and the reaction current density (j) is established based on the mass transport equations. From the j–η act plots, our results reveal that i) with the increase of HER current, the equivalent increases, which accompanies with a drift of thermodynamic equilibrium potential (Eeq) for HER decreases; ii) when η act is negative of −50 mV, the j–η act plot for HER is the same in N2 and H2 saturated solution, with a slope of 30 mV Dec−1; Our results suggest that HER activity should be compared in solutions with the same composition and at the same activation overpotential instead of at the same applied potential. Proper experimental methods for post data analysis are proposed in order to derive the intrinsic HER kinetics.

Psychological Resilience Skills Training To Improve Psychological Resilience, Self Esteem, And Quality Of Life

Background: It is expected that the quality of life of TB patients will improve after treatment, but research shows indications of emotional stress in TB patients at the end of treatment, clinical, social consequences, drug resistance, and decreased quality of life, especially psychological and social aspects. Research purpose knowing the description of psychological resilience, self esteem, quality of life of TB survivors. 
 Methods: A total of 61 TB survivors were taken by total sampling technique. 30 respondents in the experimental group were given psychological resilience skills training. Data was collected using the CD-RISC instrument, Rosenberg self-esteem scale, and WHOQOL-bref. Pre test is taken before training postData analysis used t test and regression test with SPSS 19 software.
 Results: Based on the SPSS analysis, it is known that no significant effect of psychological resilience on self esteem with p value of 0,33. Psychological resilience has a significant effect on quality of life with p value of 0,048. Self esteem has no significant effect on quality of life with p value of 0,335. Psychological resilience is more influential on social aspects than psychology on the quality of TB survivors. 
 Conclussion: Possibly related to the participating in the association of fellow TB survivors. It can also caused by the length of time to recover. Psychological resilience skills can be developed by stakeholders for TB survivors.

Volatility contagion (spillover) between Chinese and Pakistani stock markets during COVID-19: pre and post analysis of trade-level data

Volatility contagion (spillover) between Chinese and Pakistani stock markets during COVID-19: pre and post analysis of trade-level data

Volatility contagion (spillover) between Chinese and Pakistani stocks market during COVID-19: pre and post analysis of trade-level data

Volatility contagion (spillover) between Chinese and Pakistani stocks market during COVID-19: pre and post analysis of trade-level data