IntroductionTo enhance the employees’ performance, the leaders of organizations have considered the latest procedures in the current extremely competitive atmosphere. It is vocalized by Nelson and Cooper (2007) that observing the organizational behavior in a different way, causes to consider the occupation with a new look and concentrates on positive attributes of individuals and organizations without paying attention to disease or dysfunction (p. 3). Based on positive attributes, we predict that fortifying job involvement can be considered as a significant variable which influences the organization’s outcomes. As claimed by Kanungo (cited in Eldor & Harpaz, 2018), job involvement means, “cognitive or belief state of psychological identification”. Supposedly, individual’s internal cognition of activity identities or beliefs is the foundation of job involvement (Peng, 2018; Robbins & Judge, 2018, p.50). Psychologically, people are identified by their job and work activity is supposed essential to self-concept (Welbourne & Sariol, 2017; Zagenczyk, & Murrell, 2009; Ho, 2006; Carson, Carson, & Bedeian 1995). Brown (1996) noted that occupation activities swallow an enormous proportion of time; moreover, a fundamentally vital aspect of every body’s life is constituted by it. Shy, Hu, and Chuan (2018) pointed out two aspects for job involvement. The first one is the work enthusiasm level and secondly, the work identification that must be stronger than others. Typically, accumulation of workplace rewards is a subsequence of fortifying job involvement and it plays a dominant role in heightening factors e.g. continuance commitment (Dawkins, Tian, Newman, & Martin, 2017; Erdheim, Wang, & Zickar, 2006). Lambert, Qureshi, Frank, Klahm, & Smith (2018) proposed, when an individual places the job at the center of his life’s interest, his job involvement takes a high degree. The well-known saying: ‘I live, eat, and breathe my job’ describes an individual whose job involvement is strongly high (Lambert et al., 2018; Peng, 2018; Yeh, 2018; Kong, 2013; Lambert, Minor, Wells, & Hogan, 2016; Nyambegera, 2000). Overall, self-accomplishment, positive and career-oriented psychological state are established by influential job involvement (Peng, 2018).Job involvement is one of the most important attitudes that as well as job satisfaction and organizational commitment specify much researches to make their concepts understandable (Robbins & Judge, 2018, P.50). Subsequently, job involvement and organizational commitment possess reversal relationship with absenteeism and turnover (Lambert et al., 2018; Erdheim et al., 2006; Lam, Lo & Chan, 2002; Brown, 1996). Considering and developing job involvement is important because it impacts the various organizational variables such as organizational culture (Taştan & Türker, 2014; Taştan, 2013), creativity (Eldor & Harpaz, 2018), organizational commitment (Erdheim, Wang, & Zickar, 2006; Lambert et al., 2018), performance (Brown & Leigh, 1996; Nirwan, 2017) and innovative behavior (Peng, 2018). Investigating job involvement is necessary because others’ research results indicate that it is influenced by different variables e.g. employees’ character (Brown, 1996), coaching and team effectiveness (Shy et al., 2018), emotional intelligence (Yeh, 2018), leader’s creativity (Zhao & Guo, 2019), career competencies (kong, 2013), perceived organizational support (Cheng, 2011), change-oriented leadership (Mikkelsen & Olsen, 2019), psychological climate (Brown & Leigh, 1996) and job characteristics (Moynihan & Pandey, 2007). Motivation improvement is one of the factors to impact job involvement. Based on Mills (2011), inner motivation to fulfill the responsibility can be stimulus of job involvement and the combination of internal motivation and attempt, and then the proportion of job involvement will be increased (Mills, 2011). With regard to change human force to a persistent worthy capital that can add value to the organization, it is important to provide a condition for employees to work highly motivated in a safe and calm atmosphere. They must employ their maximum attempts and abilities or job involvement toward achieving organizational goals.The work-related responsibilities need a vital factor that is called motivation (Rochat & Rossier, 2016). Counseling sessions fortify attention through motivation that is effective on treatment (Ryan, Lynch, Vansteenkiste & Deci, 2011). One of the job involvement components is internal motivation and the other is supposed as the individual’s active participation in the job, physically or mentally, that is the foundation of self-esteem and self-concept which extraordinarily affect the job involvement (Ho, 2006; Pelkey, 2017; Welbourne & Sariol, 2017). Various variables have the effect on job involvement, so possessing high job involvement keeps the competitive mood in a way that the others are encouraged to enable their constructive abilities such as self-esteem (Pelkey, 2017). Motivation is assumed as the foundation of counseling and treating hopelessness. Employees’ engagement and participating in making change cause formative and long-term results (Ryan et al., 2011). According to Srivastava’s research (2014) employees’ motivation is related to the job involvement, so low burnout individuals are more job involved and organizational committed; moreover, low level of motivation is caused by high burnout. This is depicted in the research of Skipworth (2016) that there is a small or medium positive relationship between intrinsic and extrinsic motivation and satisfying job involvement or organizational commitment for who works in nontraditional organizations. According to the represented evidence, we understand that the employees who get pleasure and satisfaction out of job involvement approve their importance and value completely. So, they are more satisfied and eager to be loyal toward the job and organization (Fernet, Trépanier, Demers, & Austin, 2017). According to Awuja and Ahiakwo (2019), making change needs energy and motivation is the stimulus of it and energizes the individuals to reach the goal as well as representing the necessary actions which must be accomplished toward reaching goals. For instance, the sufficient amount of teacher’s motivation leads him to an influential job involvement and finally teaches perfectly that causes the students’ good performance. As regards, it can be noted that occupation and influential organizational or job commitment as the changeable policy can associate with motivation effectively in the job area (Fernet et al., 2017). Moreover, there is positive relationship between motivational needs and job involvement or negative relationship between motivational tension and job involvement (Awuja & Ahiakwo, 2019). In line with this result, Brown (1996) stated the individuals either are being stimulated by or drawn in their occupations deeply as well as being alienated from it not only mentally but also emotionally. Besides, internal motivation that causes work accomplishment is the real reason of job involvement (Mills, 2011). Intrinsic motivation as an internal factor is a personal intention for overcoming the job challenges and communicating with trustful colleagues. Job satisfaction comes from intrinsic motivation. There is difference between the employees who have different stimulus for being motivated. Therefore, knowing them and discovering their motivational factors are vital. The leaders can motivate the staff by intrinsic and extrinsic motivators, too (Awuja & Ahiakwo, 2019).Kiruja and Mukuru (2018) remarked that motivation as an inner stimulus or external factor helps the employees to behave particularly that finalizes rewards. Moreover, a formative component in a competitive area is motivation that can help the employees intrinsically to perform better. Productive and satisfied employees perform loyally and do not desire to change their workplace.One of the most interesting approaches to make the employees explore the career is motivational interviewing because it helps them to understand that career is the acceptance of many responsibilities- exactly something that is tough to accept (Krieshok, Motl & Rutt, 2011). Motivational interviewing is a collaborative conversational style for strengthening a person’s motivation for commitment and change (Fortune, Breckon, Norris, Eva & Frater, 2018; Rosengren, 2018, p.12; Wilcox et al., 2017, p.19). Motivational interviewing also recognizes that people have the right to self-determination, to decide whether they will or will not change, to what degree, and how they will do so. Clients are credited with autonomy to make the correct decisions for themselves in every session of counseling (Corcoran, 2016, p.1). As a clinical approach to cure substance use disorders, motivational interviewing was developed in the 1980s (Laws et al., 2018; Wilcox et al., 2017, p.19; Fortune et al., 2018). Health care uses the benefits of motivational interviewing; moreover, interestingly, the other organizations and systems, such as legal system utilize it to develop change in behavior which can support others’ well-being (Wilcox et al., 2017, p.19).Contribution in adapting, engaging and searching can develop ideal manner in employees. But, what is the best method to stimulate workers to participate more and more in their jobs? (Krieshok et al., 2011) Britt, Sawatzky & Swibaker’s research (2018) about motivational interviewing toward enhancing employment concluded that in accordance with job, motivational interviewing is influential in three areas: increasing job motivation, participating in job activities and continuing the job. Motivated employees are known as the creative, reactive and enthusiastic people and committed to their organizations and customers, so their involvement has significant impact on the workplace (Kiruja & Mukuru, 2018). The purpose of motivational interviewing is change that some of the individuals need it. The evidences illustrate that motivational interviewing is an intervention that is influential alone; besides, it is able to impact the employees’ fulfillment (Gance-Cleveland et al., 2017). One of the significant motivational interviewing principles is creating conflict or disagreement in staff’s condition. The time difference is provided for the staff so that they can witness a big difference between their current behavior and future goals. The motivational interviewing psychologist represents an active role in creating these differences by listening skills (Glynn & Moyers, 2010). It is expected to represent the effectiveness of motivational interviewing-lead on several sorts of situations; besides, the represented approach can create trust and profitable relationships between the individuals or make the team accomplishment better and more important than that increase the employees’ satisfaction, deduct turnover and develop the performance of the organization (Wilcox, Kersh & Jenkins, 2017, p.29).Accordingly, the motivational interviewing method is used as an organizational variable such as leadership because of its specific qualities. It is necessary to observe three leadership teams to recognize when facilitating adapt goals with the employees:1. Taking organizational transition is a process.2. Employees’ freak is supposed normally.3. Employees must find their own alternatives to take adaptation goals (Fields, 2006, P. 5).The purpose of current research exposes the effect of group counseling based on motivational interviewing on job involvement. According to the evidences, we claim that developing the organization toward goal achievement is one of the consequences of improving employees’ job involvement. Mills (2011) claims that if the employees involve in their job, the organization reaches its goal mostly; moreover, selecting the appropriate team of staff makes the achievement easier.Although, any researches haven’t done yet to embody the impact of mentioned interference on employees’ job involvement directly, the process attracts researchers’ attitude and create this question, is it possible the group counseling based on motivational interviewing influences the employees’ job involvement?

This paper presents a comprehensive review of the robustness of hand gesture recognition systems in low light intensity environments spanning the years 2018 to 2023. The primary objective is to assess the progress made during this period and identify areas requiring further attention. An extraction of 20 relevant journals from reputable online databases was conducted using selected keywords. Most of the reviewed articles delve into three crucial aspects of hand gesture recognition systems: data acquisition, data environment, and hand gesture representation. The system performance evaluation reveals that machine learning models achieve recognition accuracy between 94% and 98%, while computer vision models report accuracy within the range of 90% to 95%. The deep learning approach shows a broader accuracy range, spanning from 90% to 98%. Notably, the studies reviewed utilized datasets comprising 37 hand gestures, including 26 letters of American Sign Language (ASL) and numeric gestures ranging from 0 to 9. This paper sheds light on the current state of hand gesture recognition in low light environments and provides insights into potential opportunities for further research and development.

A document by Fernando Jaramillo. Click on the document to view its contents.

Air pollution has emerged as a critical global concern in our era due to its far-reaching impacts on the environment and human health. Air pollutants including particulate matter, carbon monoxide, ozone, nitrogen dioxide, and sulfur dioxide, are of immediate concern and are sources of morbidity and mortality. Additionally, air pollutants pose severe threats to human health, encompassing acute and chronic conditions. Particulate matter, composed of fine particles and aerosols, heightens the risk of respiratory diseases like asthma and chronic obstructive pulmonary disease (COPD), with long-term exposure linked to lung cancer. Carbon monoxide (CO), emitted from combustion, induces hypoxia, causing headaches, fatigue, and, in severe cases, cardiovascular complications and fatalities. Ground level ozone exacerbates respiratory distress, aggravates asthma, and impairs lung function. Nitrogen dioxide (NO2) from vehicles and industries irritates the respiratory system, contributing to respiratory diseases, while sulfur dioxide (SO2) from fossil fuels worsens respiratory conditions. Synergistic effects amplify health risks, particularly for vulnerable populations. Addressing these threats necessitates comprehensive strategies to reduce emissions, improve air quality, and protect the health of diverse communities.

This is a lesson prepared to teach the programming concept - Algorithm, to 6 - 8 year old students from Sri Lanka.  The students will be learning a concept that is important in science, engineering, technology and mathematics using puzzles. This lesson also focus on the understanding the use of algorithms in their daily activities. Objectives:Definition of Algorithm.Introducing the importance of Algorithms in the problem-solving and programming.Engage in a problem solving activity by implementing an algorithm to solve a specific task.Reflection on the use of algorithms in daily life.Materials:Colored Sheets of 5 colors - size 420mm x 594mm/A2TapeIndex cardsA reward/ toyA white boardMarkers/pensIntroduction - 15 mins :Engage: The lesson will be started with basic discussion about the term "Algorithm". Ask the student if they have heard the term before or have they used algorithms in their day to day lives. Ask them what they think it means. Ask them if they have ever followed a recipe or taken/given directions or if they have ever seen someone following a recipe or taking/giving directions.Define: Provide a simple definition for an Algorithm." An Algorithm is a list of steps to finish a task""  An algorithm is a step-by-step set of instructions or rules to solve a problem"   Activity - 20 mins: Unplugged Algorithm Activity: Paste the colored sheets on the floor in a similar pattern as shown in the sample image.

Software Defined Networks (SDN) provide rapid configuration, scalability, and management through a dynamic, programmable architecture that surpasses traditional network limitations. However, detecting Distributed Denial of Service (DDoS) attacks remains challenging, threatening both traditional and SDN-based networks. Machine Learning (ML) and Deep Learning (DL) technologies in conjunction with SDN have shown significant potential in effectively countering these threats. Prior studies primarily addressed high-rate DDoS attacks, neglecting low-rate DDoS attacks that resemble legitimate traffic, and often using outdated datasets. While researchers employ various offline learning algorithms to identify DDoS attacks, online learning classifiers remain underexplored. Our goal is to offer an intrusion detection model tailored to SDN networks, using the online passive-aggressive classifier. The proposed model achieves a 99.7% average detection rate for normal vs. DDoS network traffic, outperforming similar models on multiple datasets, including (CICDDoS2019, and InSDN. slow-read-DDoS), effectively detecting and mitigating DDoS attacks.

A document by En Zhou Ye. Click on the document to view its contents.

A document by Moshe Segal. Click on the document to view its contents.

This is a lesson prepared to teach the programming concept - Algorithm, to 6 - 8 year old students from Sri Lanka.  The students will be learning a concept that is important in science, engineering, technology and mathematics using puzzles. This lesson also focus on the understanding the use of algorithms in their daily activities. Objectives:Definition of Algorithm.Introducing the importance of Algorithms in the problem-solving and programming.Engage in a problem solving activity by implementing an algorithm to solve a specific task.Reflection on the use of algorithms in daily life.Materials:Colored Sheets of 5 colors - size 420mm x 594mm/A2TapeIndex cardsA reward/ toyA white boardMarkers/pensIntroduction - 15 mins :Engage: The lesson will be started with basic discussion about the term "Algorithm". Ask the student if they have heard the term before or have they used algorithms in their day to day lives. Ask them what they think it means. Ask them if they have ever followed a recipe or taken/given directions or if they have ever seen someone following a recipe or taking/giving directions.Define: Provide a simple definition for an Algorithm." An Algorithm is a list of steps to finish a task""  An algorithm is a step-by-step set of instructions or rules to solve a problem"   Activity - 20 mins: Unplugged Algorithm Activity: Paste the colored sheets on the floor in a similar pattern as shown in the sample image.

Short title: Buccal nitroglycerin ointment administration for acute pulmonary edemaAuthor: Mohammad Reza Movahed, MD, PhD 1,2University of Arizona, Phoenix, AZ1 University of Arizona Sarver Heart Center, Tucson2Correspondent:M Reza Movahed, MD, PhD, FACP, FACC, FSCAI, FCCPClinical Professor of Medicine, University of Arizona Sarver Heart Center, TucsonClinical Professor of Medicine, University of Arizona , Phoenix1501 N Campbell AvenueTucson, AZ 85724Tel: 949 400 0091Email: rmova@aol.comConflict of interest: NoneFunding: NoneKey words: congestive heart failure; systolic heart failure; diastolic heart failure; pulmonary edema; hypoxic respiratory failure; acute pulmonary edema; acute congestive heart failure

O presente trabalho apresenta uma revisão integrativa de estudos publicados por pesquisadores/as brasileiros/as referentes à compreensão metafórica por indivíduos diagnosticados com transtorno do espectro autista (TEA). O objetivo da pesquisa foi verificar a existência de estudos experimentais  de base psicolinguística produzidos em âmbito nacional que investigam a compreensão de metáforas por falantes nativos de português brasileiro com TEA. A busca por artigos se deu através de três bancos de dados de referência brasileiros – Portal de Periódicos da CAPES, Scopus e Scielo –, por meio de uma pesquisa avançada por trabalhos que apresentassem os termos metáfora e autismo ou transtorno do espectro autista. No total, foram encontrados somente 3 artigos que cumpriam os pré-requisitos estabelecidos. Os resultados encontrados evidenciam a necessidade premente de se desenvolverem pesquisas neste campo em âmbito nacional no sentido de melhor compreender esse fenômeno para, futuramente, desenvolver propostas de intervenções que contribuam para a qualidade de vida de sujeitos diagnosticados com TEA. This paper presents an integrative review of studies published by Brazilian researchers on metaphorical comprehension by individuals diagnosed with autism spectrum disorder (ASD). The aim of the research was to verify the existence of psycholinguistically-based experimental studies conducted in Brazil that investigate the comprehension of metaphors by native speakers of Brazilian Portuguese with ASD. Research was conducted for articles in three Brazilian reference databases – Portal de Periódicos da CAPES, Scopus and Scielo – through an advanced search tool, and papers were selected that presented the terms metaphor and autism or autism spectrum disorder. In total, only 3 articles were found that met the established criteria. The results show that there is an urgent need to develop research in this field to better understand this phenomenon and develop proposals for interventions that contribute to the quality of life of people diagnosed with ASD.

Authors: *Muneer Yaqub1, Abdulbasit Balogun Opeyemi2, Gaius BalaAffiliations: 1. The University of Texas at Dallas, Richardson, Texas, USA 2. School of Medical Laboratory sciences, Usmanu Danfodiyo University Sokoto, Nigeria

In arithmetic coding, the input data is mapped to a small subinterval within the interval [0, 1). In the conventional implementation, a rational number is selected from this, which can be represented as a fraction with a power of two in the denominator. Only the numerator of this fraction is saved in the compressed file because the power of the denominator corresponds to the number of bits in the numerator and can therefore be reconstructed from it. This paper introduces a new variant that instead uses the Stern-Brocot tree and the Farey addition to find the rational number that has the smallest possible denominator within the same interval. Now the denominator must be stored in the same way as the numerator, but the numerator and denominator together have only about as many binary digits as the number obtained using the conventional method. In around one in four cases, the result of the new approach is even shorter than the conventional binary number. The results show that this new method is not only interesting for theoretical reasons, but even has the potential to outperform established methods.

Luciana Tellería1, Rodrigo Calbimonte1 & Flavia Montaño-Centellas2,3*1 Carrera de Biología, Universidad Mayor de San Andrés, La Paz, Bolivia.2 Instituto de Ecología, Universidad Mayor de San Andrés, La Paz, Bolivia.3 Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803.*Corresponding autor: flamontano@gmail.comRunning head: Nectar robbing by the Red-tailed CometAbstract · Nectar robbing by hummingbirds, the extraction of nectar using perforations instead of the corolla, is seldom documented in the literature. Here, we present the first photographic record of nectar robbing by the Red-tailed Comet Sappho sparganurus in Bolivia and examine published and photographic evidence of this behavior. We found no published evidence of nectar robbing by Red-tailed Comets in peer-reviewed literature. However, we found that about 4% of the photographs of hummingbird-flower interactions involving this species on citizen science platforms showed clear nectar robbing behavior. Our results suggest that nectar robbing is not an uncommon behavior for the Red-tailed Comet and highlight the hidden, yet immense, value of citizen science photographic databases to document avian natural history and behavior.

Nonlinear optimization problems with cardinality constraints and risk measurements, particularly in the fields such as finance and risk management, have posed significant challenges. Portfolio optimization under these constraints requires effective algorithms and methodologies to improve performance. Thus, this study aimed to investigate in nonlinear optimization problems with cardinality constraints and risk measurements in fields like finance and risk management. Indeed, by using various algorithms and methodologies, this study aimed to improve the performance of portfolio optimization under these constraints. To measurement risk in portfolio programing, deemed as an application in nonlinear problems with cardinality constraints, VaR (value at risk), CVaR (conditional value at risk), RVaR (robust value at risk), and RCVaR (robust conditional value at risk) were used. Regularization techniques played a crucial role in optimizing non-smooth problems, addressing challenges arising from the non-smoothness of the constraints, thereby enhancing algorithm performance. By using some regularization algorithms, such as Scholtes, Kanzow-Schwartz, and Bordakov methods, an improvement in performance was obtained. Notably, sequential quadratic programming (SQP), which is an iterative optimization technique, was used to solve nonlinear programming problems by approximating the objective and constraints using quadratic functions. After a comparison of algorithms' performance was explored, the experiments indicated a significant enhancement in the performance of the SQP algorithm by using the Scholtes regularization technique. Thus, these findings show that SQP can be a promise method to solving this classification of cardinality-constraints nonlinear problems. The study introduces innovative optimization solutions to improve algorithmic performance in complex problems, contributing to advancements in finance and risk management approaches.

A document by Sandy Hardian Susanto Herho. Click on the document to view its contents.

The use of specular reflecting passive electromagnetic skins (EMSs) in NLOS wireless backhauling at carrier frequencies ranging from sub-6GHz to W-band is dealt with. A set of design guidelines is derived to predict the relation between the meta-atom layout and the NLOS link efficiency as well as the scalability of the EMS-based backhauling to different carrier/link-distances. The results of several numerical experiments are reported and the total path attenuation (TPA) is evaluated by varying the EMS layout, the EMS material, the range of the wireless link, and the incidence angle from the transmitter in comparison with that from traditional flat conducting screens (PCSs), as well. The reliability and the effectiveness of the proposed EMS-based solution for NLOS wireless links are validated through both full-wave numerical simulations and experimental measurements on an EMS prototype in a realistic environment.

An accurate spatial and temporal representation of rainfall is essential for hydrological assessments and water resources management. Rainfall is monitored in India’s mountainous Western Ghats region via in-situ rainfall gauging stations maintained by the Indian Meteorological Department (IMD). However, the network is sparse, and significant periods of data are missing. Furthermore, the IMD gridded rainfall dataset is known to underestimate the depth of rainfall at the high altitudes within this region. In this study, rainfall estimated by the IMD grids and from remote sensing using the CHIRPS (0.25- and 0.05- degree), MSWEP and PERSIANN datasets are compared to the IMD in-situ gauged rainfall within the Western Ghats using a point-to-pixel analysis. The GWAVA model is utilised to determine the effect of the selected rainfall input datasets on representing wider water resources. It was found that the average ensemble provided the best representation of the in-situ gauged and catchment rainfall and a better representation than the IMD grids. It remains critical for water resources management to ensure that in-situ rainfall gauging networks are maintained. In-situ data sources of high confidence remain important for the continuous development and ground-truthing of different rainfall datasets.

A document by Ramitha Kalhara Dissanayake Ralalage. Click on the document to view its contents.

Arctic sea ice is retreating, thinning, and exhibiting increased mobility. In the Beaufort Gyre (BG), liquid freshwater content (FWC) has increased by 40\% in the last two decades, with sea ice melting being a primary contributor. This study utilizes satellite observations of sea surface salinity (SSS) and sea ice concentration, along with model-based sea ice thickness from 2011 to 2019. The aim is to investigate the sea ice-SSS relationship at different scales in the Arctic and understand the sea-ice meltwater dynamics in the BG. Our findings reveal a strong synchrony and positive correlation between sea ice area and SSS in the Arctic Ocean. In September, when the BG exhibits the largest ice-free ocean surface, a noticeable release of freshwater from sea ice melting occurs, a phenomenon not accurately reproduced by the models. The SMOS (Soil Moisture and Ocean Salinity) mission proves valuable in detecting meltwater lenses (MWL) originating from sea ice melting. These MWLs exhibit mean SSS ranging from 19 psu at the begining of sea ice retreat to 25 psu before sea ice formation. Wind-driven anticyclonic eddies can trap MWLs, preserving the freshest SSS imprints on the sea surface for up to 10 days. Furthermore, events of sea surface salinification following sea ice formation suggest that SMOS SSS might be capturing information on brine rejection. The daily evolution of sea ice-SSS within the MWLs demonstrates a tight correlation between both variables after sea ice melting and just before sea ice formation, indicating a transient period in between.

  This study presents a novel methodology for extracting latent variables from high-dimensional sparse data, particularly emphasizing spatial distributions such as precipitation distribution. This approach utilizes multidimensional scaling with a distance matrix derived from a new similarity metric, the Unbalanced Optimal Transport Score (UOTS). UOTS effectively captures discrepancies in spatial distributions while preserving physical units. This is similar to mean absolute error, however it considers location errors, providing a more robust measure crucial for understanding differences between observations, forecasts, and ensembles. Probability distribution estimation of these latent variables enhances the analytical utility, quantifying ensemble characteristics. The adaptability of the method to spatiotemporal data and its ability to handle errors suggest its potential as a promising tool for diverse research applications.

A physician's reflection on how we can look healthy on the outside yet on the inside be suffering a great tragedy, and in these situations sometimes the only thing we can do is create a meaningful human connection. A laugh and a smile can have timeless value.

In this paper, the nonlinear extended state observer (NESO) is proposed to estimate the state-of-charge (SOC) of the Lithium-ion batteries (LIBs). The NESO is designed based on the first-order equivalent circuit model (ECM) to estimate the total disturbance of the battery model and compensate them as the new extended state, which can achieve the active disturbance rejection to estimate the battery state accurately. Furthermore, the stability of the NESO is proven, and estimation performance of the observer is verified under different ambient temperatures, testing driving and different noise levels. The SOC estimation results indicate that the NESO can obtain accurate estimation values and strong robustness against different disturbances, even though all validation conditions use constant battery value of the first-order ECM. In addition, compared with other common estimation methods, the NESO exhibits a faster convergence time and more accurate estimation results.

Cosmic radiation on Earth responds to heliospheric, geomagnetic, atmospheric, and lithospheric changes. In order to use its signal for soil hydrological monitoring, the signal of thermal and epithermal neutron detectors needs to be corrected for external influencing factors. However, theories about the neutron response to soil water, air pressure, air humidity, and incoming cosmic radiation are still under debate. To challenge these theories, we isolated the neutron response from almost any terrestrial changes by operating bare and moderated neutron detectors in a buoy on a lake in Germany from July 15 to December 02, 2014. We found that the count rate over water has been better predicted by a recent theory compared to the traditional approach. We further found strong linear correlation parameters to air pressure and air humidity for epithermal neutrons, while thermal neutrons responded differently. Correction for incoming radiation proved to be necessary for both thermal and epithermal neutrons, for which we tested different neutron monitors and correction methods. Here, the conventional approach worked best with the Jungfraujoch monitor in Switzerland, while the approach from a recent study was able to adequately rescale data from more remote neutron monitors. However, no approach was able to sufficiently remove the signal from a major Forbush decrease event, to which thermal and epithermal neutrons showed a comparatively strong response. The buoy detector experiment provided a unique dataset for empirical testing of traditional and new theories on CRNS. It could serve as a local alternative to reference data from remote neutron monitors.