Target Set Research Articles

Investigation of alternative vehicle applications for reducing greenhouse gas emissions in urban public transport: The case of Adana province

Passenger cars, trucks, commercial airplanes, and railways all contribute to greenhouse gas emissions as part of the transportation sector. The usage of fossil fuels such as gasoline and diesel emits exhaust gases commonly referred to as greenhouse gases (GHGs) into the atmosphere. The buildup of these greenhouse gases in the atmosphere is responsible for global warming, a phenomenon that is becoming increasingly pronounced in today’s climate. In response to the GHG problem, cities have started setting targets to reduce their emission values. Adana is one of the cities that has set reduction targets. In all of the studies forming the basis of this research, the potential for transitioning buses and minibuses used in public transportation in Adana to alternative vehicles is investigated, with a focus on reducing greenhouse gas emissions. This study includes a comparison between electric, compressed natural gas (CNG), hydrogen and conventional vehicles, considering various parameters such as fuel economy estimates, vehicle size, and emission calculations. The research delves into greenhouse gas emission calculations specific to the Adana province, along with potential alternative applications in public transportation. Within the province, the transportation sector accounts for 27% of the total city inventory’s emissions. This study shows that converting the existing urban public transport fleet to alternative buses can lead an impressive reduction in greenhouse gas emissions as 81.93% with electric car, while hydrogen vehicles achieve a commendable 57.37% decrease. This underscores the substantial potential of electric and hydrogen-powered vehicles to lead to a significant reduction in transportation-related carbon emissions in the city. Consequently, the research places significant emphasis on addressing the transportation sector, which stands out as a primary contributor to emissions.

Performance Analysis Using Balance Score Card (BSC) at the Banyuwangi State Treasury Service Office: A Phenomenology Study

This study aims to explore the application of the four perspectives of the Balanced Scorecard in evaluating the performance of the Treasury Service Office (KPPN) Banyuwangi. The findings of this research are expected to contribute theoretically to the development of management science and serve as a reference for future research, particularly on the fourperspective Balanced Scorecard model for assessing the performance of public sector organizations (government agencies). This qualitative research employs a phenomenological approach to examine the concept of the Balanced Scorecard in evaluating the performance of one government agency under the Ministry of Finance, namely KPPN Banyuwangi. Data were collected directly through interviews and observations, as well as indirectly through performance reports, survey results, and various supporting references. The results of the research indicate that KPPN Banyuwangi achieved good performance based on the Balanced Scorecard with Key Performance Indicators in 2022, which include four analytical aspects: stakeholder perspective with a weight of 30% and a total score of 105.91, customer perspective with a weight of 20% and a total score of 104.30, internal perspective with a weight of 25% and a total score of 109.81, and learning and growth perspective with a weight of 25% and a total score of 112.04. Overall, the Organizational Performance Indicator Achievement Index in 2022 reached 108.09%, with all Key Performance Indicators (KPIs) surpassing the set targets.

Clinical neuromodulatory effects of deep brain stimulation in disorder of consciousness: A literature review.

The management of patients with disorders of consciousness (DOC) presents substantial challenges in clinical practice. Deep brain stimulation (DBS) has emerged as a potential therapeutic approach, but the lack of standardized regulatory parameters for DBS in DOC hinders definitive conclusions. This comprehensive review aims to provide a detailed summary of the current issues concerning patient selection, target setting, and modulation parameters in clinical studies investigating the application of DBS for DOC patients. A meticulous systematic analysis of the literatures was conducted, encompassing articles published from 1968 to April 2023, retrieved from reputable databases (PubMed, Embase, Medline, and Web of Science). The systematic analysis of 21 eligible articles, involving 146 patients with DOC resulting from acquired brain injury or other disorders, revealed significant insights. The most frequently targeted regions were the Centromedian-parafascicular complex (CM-pf) nuclei and central thalamus (CT), both recognized for their role in regulating consciousness. However, other targets have also been explored in different studies. The stimulation frequency was predominantly set at 25 or 100 Hz, with pulse width of 120 μs, and voltages ranged from 0 to 4 V. These parameters were customized based on individual patient responses and evaluations. The overall clinical efficacy rate in all included studies was 39.7%, indicating a positive effect of DBS in a subset of DOC patients. Nonetheless, the assessment methods, follow-up durations, and outcome measures varied across studies, potentially contributing to the variability in reported efficacy rates. Despite the challenges arising from the lack of standardized parameters, DBS shows promising potential as a therapeutic option for patients with DOC. However, there still remains the need for standardized protocols and assessment methods, which are crucial to deepen the understanding and optimizing the therapeutic potential of DBS in this specific patient population.

A stochastic target problem for branching diffusion processes

We consider an optimal stochastic target problem for branching diffusion processes. This problem consists in finding the minimal condition for which a control allows the underlying branching process to reach a target set at a finite terminal time for each of its branches. This problem is motivated by an example from fintech where we look for the super-replication price of options on blockchain-based cryptocurrencies. We first state a dynamic programming principle for the value function of the stochastic target problem. Next, we show that the value function can be simplified into a novel function with the use of a finite-dimensional argument through a concept known as the branching property. Under wide conditions, this last function is shown to be the unique viscosity solution to an HJB variational inequality.

Exploring the Emotional Characteristics of Chinese Language Literature Based on the Thinking Operation Model

Abstract In this paper, each text is mapped as a point in a multidimensional vector space in a thought operation model to represent the emotion feature vocabulary in Chinese language literary works in the form of word embedding. The bootstrapping technique is utilized to collect initial seed set vocabulary and target vocabulary, and a corpus of literary works with six basic emotion categories is established. Based on the emotional features of Chinese language literary works, the memory network model for textual emotion analysis based on multiple attention is constructed, and the textual emotion features of Chinese language literary works are empirically analyzed. The results show that the precision is 82.19%, 93.12%, and 94.1%, and the F1Score is 81.93%, 93.4%, and 93.76%, respectively, and the precision and F1Score are better than the effect of the control group model, i.e., it indicates that the effect of sentiment analysis is more excellent. The ratio values of positive emotion, negative emotion, and neutral emotion are, respectively, 63.16%, 15.49%, and 21.35%, i.e., the expression of emotion in Chinese language literary works is more rational. This study provides new perspectives and theoretical references for the study of traditional literary works and has the potential to expand the study in depth.

Comparison of the Use of Renewable Energy Sources (Res) by Poland and Latvia in the Perspective of the Environmental Objectives Set by the European Union

The objective of this article is to present an analysis of the utilization of renewable energy sources in Latvia and Poland since their accession to the European Union (EU), and to evaluate the progress made in meeting the environmental targets established by the EU through the implementation of Directive 2009/28/EC. The analysis is based on data obtained from the "Our World in Data" database as well as government documents. The findings reveal that while Latvia has successfully met the EU requirements, Poland has yet to achieve the set targets. However, Poland efforts in the development of renewable energy sources indicate a promising trajectory, mirroring those undertaken by Latvia. These implemented measures can serve as a valuable reference for other countries in their pursuit of a greener future.

AVAILABILITY OF GREEN OPEN SPACE IN MEDAN CITY

Urban development often prioritizes the economic sector over green open spaces (RTH), which significantly impacts environmental sustainability. Medan City faces challenges in meeting RTH targets, particularly in the context of rapid population growth and limited urban land. This research explores the availability and policies of RTH in Medan City and identifies factors influencing the lack of RTH. The research findings indicate that the implementation of RTH policies in Medan City is still far from the set targets. Despite efforts such as land acquisition and the addition of RTH, deficiencies persist, mainly concerning the community's understanding of the importance of RTH. Therefore, this study recommends an approach of intensification and extensification in RTH development, involving community participation, integrated planning, and the application of Green City concepts to achieve environmental sustainability and community well-being in Medan City.

SetDB1 and Su(var)3-9 are essential for late stages of larval development of Drosophila melanogaster.

Methylation of H3K9 histone residue is a marker of gene silencing in eukaryotes. Three enzymes responsible for adding this modification - G9a, SetDB1/Egg, and Su(var)3-9 - are known in Drosophila. To understand how simultaneous mutations of SetDB1 and Su(var)3-9 may affect the fly development, appropriate combinations were obtained. Double mutants egg; Su(var)3-9 displayed pronounced embryonic lethality, slower larval growth and died before or during metamorphosis. Analysis of transcription in larval salivary glands and wing imaginal disks indicated that the effect of double mutation is tissue-specific. In salivary gland chromosomes, affected genes display low H3K9me2 enrichment and are rarely bound by SetDB1 or Su(var)3-9. We suppose that each of these enzymes directly or indirectly controls its own set of gene targets in different organs, and double mutation results in an imbalanced developmental program. This also indicates that SetDB1 and Su(var)3-9 may affect transcription via H3K9-independent mechanisms. Unexpectedly, in double and triple mutants, amount of di- and tri-methylated H3K9 is drastically reduced, but not completely absent. We hypothesize that this residual methylation implies the existence of additional H3K9-specific methyltransferase in Drosophila.

Using Big Data to enhance data envelopment analysis of retail store productivity

PurposeThe concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.Design/methodology/approachThe methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.FindingsThe proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.Practical implicationsThe use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.Originality/valueThis article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

Academic Library: A Managerial Review

This paper Academic Library: A Managerial Review explores management of academic libraries. The paper looks at academic library as an information center established in tertiary institution to support the mission of their parent institutions, which has to do with teaching, learning and research with the available information resources. The paper further defines academic library management as an efficient utilization of library resources to achieve the organizations objective and also as a process of getting things done through an individual, a group or people, to accomplish set targets. The paper looks at an academic library management and states that the extent, to which the academic library is able to perform effectively, depends so much on its managerial competence. This paper discusses also the origin of academic library, library management in terms of its functions such as staffing, organizational structure, funding, collection development and challenges among others. The paper concludes with recommendations that funding library, training of library staff, and equipping the organization with modern facilities with the managerial competence of librarian will help for smooth functioning of library.

Enrichment of the Local Synaptic Translatome for Genetic Risk Associated With Schizophrenia and Autism Spectrum Disorder

BackgroundGenes that encode synaptic proteins or messenger RNA targets of the RNA-binding protein FMRP (fragile X messenger ribonucleoprotein) have been linked to schizophrenia and autism spectrum disorder (ASD) through the enrichment of genetic variants that confer risk for these disorders. FMRP binds many transcripts with synaptic functions and is thought to regulate their local translation, a process that enables rapid and compartmentalized protein synthesis required for development and plasticity. MethodsWe used summary statistics from large-scale genome-wide association studies of schizophrenia (74,776 cases, 101,023 controls) and ASD (18,381 cases, 27,969 controls) to test the hypothesis that the subset of synaptic genes that encode localized transcripts is more strongly associated with each disorder than nonlocalized transcripts. We also postulated that this subset of synaptic genes is responsible for associations attributed to FMRP targets. ResultsSchizophrenia associations were enriched in genes encoding localized synaptic transcripts compared to the remaining synaptic genes or to the remaining localized transcripts; this also applied to ASD associations, although only for transcripts observed after stimulation by fear conditioning. The genetic associations with either disorder captured by these gene sets were independent of those derived from FMRP targets. Schizophrenia association was related to FMRP interactions with messenger RNAs in somata, but not in dendrites, while ASD association was related to FMRP binding in either compartment. ConclusionsOur data suggest that synaptic transcripts capable of local translation are particularly relevant to the pathogenesis of schizophrenia and ASD, but they do not characterize the associations attributed to current sets of FMRP targets.

A Flexibility Platform for Managing Outages and Ensuring the Power System’s Resilience during Extreme Weather Conditions

It is challenging for the European power system to exactly predict RES output and match energy production with demand due to changes in wind and sun intensity and the unavoidable disruptions caused by severe weather conditions. Therefore, in order to address the so-called “flexibility challenge” and implement the variable RES production, the European Union needs flexible solutions. In order to accommodate quicker reactions, compared to those performed today, and the adaptive exploitation of flexibility, grid operators must adjust their operational business model, as the electrical grid transitions from a fully centralized to a largely decentralized system. OneNet aspires to complete this crucial step by setting up a new generation of grid services that can fully utilize distributed generation, storage, and demand responses while also guaranteeing fair, open, and transparent conditions for the consumer. Using AI methods and a cloud-computing approach, the current work anticipates that active management of the power system for TSO–DSO coordination will be improved by the web-based client-server application F-channel. In the current work, a user’s experience with the platform for a Business Use Case (BUC) under the scenario of severe weather conditions is presented. The current work aims to increase the reliability of outage and maintenance plans for the system operators (SOs) by granting them a more accurate insight into the conditions under which the system may be forced to operate in the upcoming period and the challenges that it might face based on those conditions. In this way, the methodology applied in this case could, via AI-driven data exchange and analyses, help SOs change the maintenance and outage plans so the potential grave consequences for the system can be avoided. The SOs will have accurate forecasts of the relevant weather parameters at their disposal that will be used in order to achieve the set targets. The main results of the presented work are that it has a major contribution to the optimal allocation of the available resources, ensures the voltage and frequency stability of the system, and provides an early warning for hazardous power system regimes.

Process Management Practice Analysis on Organizational Performance Mediated by Knowledge Creation

Knowledge is an important resource that supports process management to produce efficient and effective products and services. The research objective is to examine the influence of process management on performance through the role of knowledge creation in the future of new normal. Survey method with saturated sample was used for data collection on 126 head of study programs at public and private universities in the city of Semarang. Partial Least Square-Structural Equation Modeling (PLS-SEM) approach was used to analyze the data. The results of the study found that process management has no direct effect on organizational performance and knowledge creation directly affects performance. Tests indirectly show that the knowledge creation shown to mediate the effect of process management on organizational performance. Implications of research for leaders as a consideration in the implementation of process management practices and knowledge creation in the new normal era of the organization. Suggestions for future research should use a longitudinal design, so that studies can be developed and explored more deeply and prepare other techniques or strategies as alternative solutions in data collection so that they are in accordance with the set targets

CircRNA-miRNA-mRNA interactome analysis in endometrial cancer

In recent years, exploring the potential of miRNAs as novel diagnostic, prognostic and diagnostic markers have gained much attention. In current study, we conducted an in-depth circRNA-miRNA-mRNA interactome to reveal significant molecular processes and biological pathways putatively associated with endometrial cancer (EC). Firstly, we retrieved two circRNAs from circad, hsa_circ_0002577 & hsa_circ_0109046, based on their association with the EC. Subsequently, we predicted miRNAs sponging sites in the two circRNAs and the potential target mRNAs of the predicted miRNAs. Sequestered miRNAs target a number of oncogenes (CBL, MET, KRAS), tumor suppressor (CFT R), receptor protein kinases & GT Pase (MET, KRAS, RAB1B), methyltransferases (SET D8), receptors associated factors (T RAF2, GRB2), growth factors (FGF20), autophagy (BECN1, AT G14), apoptotic regulators (BCL2), transcription factors (T Fs) (CREB1, RUNX1, RUNX2) and gene regulators (CCND1, HIF1A); and others, including some novel gene candidates (CREB1, FGF20, IFI27), that have never been implicated in EC earlier. The expression of hsa-miR-433-3p showed significant predictive relevance (Fold Change = 1.8, AUC = 0.736, Mann-Whitney test p-value = 6.1 e- 14) suggesting its predictive relevance in assessing patients’ response to chemotherapy. The hsamiR- 188-3p targets autophagic and apoptotic regulators and its upregulation in endometriosis may be used as for the early stage diagnostic purpose. The hsa-miR-502-5p targets SET D8, T RAF2 and others and suggests additional genomic/epigenomic molecular targets for promising therapeutic interventions in EC. Predicted miRNAs target a number of mRNAs having varied functional impacts and offer an in-depth mechanistic insights for expatiating the biological and regulatory role in EC. Communicated by Ramaswamy H. Sarma

Treat-to-Target in Atopic Dermatitis.

Atopic dermatitis is one of the most common inflammatory skin diseases among children and adults. Over the last 5 years, the armamentarium for the treatment of this disease, with both topical and systemic drugs, has increased. Treat-to-target is basically the concept where a treatment goal and a time frame for that goal is set at initiation of a new treatment, and if the goals are not achieved in time, treatment will be adjusted. In clinical trials, treatment targets are based on scoring systems for disease severity as recommended by the Harmonizing Outcome Measure for Eczema (HOME) initiative, with the primary endpoint being a reduction of at least 75% of the baseline Eczema Area and Severity Index (EASI) score (EASI-75). The question, however, is if these are useful targets in real-world settings and how this should be implemented in everyday clinical practice. In rheumatology, setting a measurable target and a time frame for an instigated therapy has been shown to lead to more efficient and successful treatment. For atopic dermatitis, the instruments recommended by HOME form the core outcome measures for the treat-to-target frameworks published to date, which are based on expert consensus and Delphi processes. Although atopic dermatitis patients have a high risk of co-morbidities, including physical, psychological and socioeconomic, instruments to measure the severity of co-morbidities have not been included in these existing frameworks. In order to apply a treat-to-target strategy that is meaningful for both the patient and the doctor, validated tools for the measurement of treatment effect on co-morbidities exist and should be included in a shared decision-making process with the individual patient when choosing which targets to aim for and what should be considered treatment success. An obvious limitation for the implementation of a treat-to-target strategy in the clinical setting with atopic dermatitis is that retrieving the data needed is very time consuming. This could to some degree be mitigated by the use of electronic applications in which patients could report their outcomes.

Insight into Spatially Colored Stochastic Heat Equation: Temporal Fractal Nature of the Solution

In this paper, the solution to a spatially colored stochastic heat equation (SHE) is studied. This solution is a random function of time and space. For a fixed point in space, the resulting random function of time has exact, dimension-dependent, global continuity moduli, and laws of the iterated logarithm (LILs). It is obtained that the set of fast points at which LILs fail in this process, and occur infinitely often, is a random fractal, the size of which is evaluated by its Hausdorff dimension. These points of this process are everywhere dense with the power of the continuum almost surely, and their hitting probabilities are determined by the packing dimension dimP(E) of the target set E.

Advantages of hybrid positron sources with granular converters

The interest in crystal effects and more precisely for channeling radiation in axially oriented crystals is underlined. An association of a photon radiator using a crystal followed by an amorphous converter may have advantages concerning heating considerations. Such a set of targets, known as a hybrid source has been already investigated and experimental results gathered at KEK are presented. As the heating load with the accompanying thermal stresses have to be studied, variants for the amorphous converter have been considered and also realized: these variants are using small spheres of high Z material, as tungsten: they are providing a better heat dissipation and lower thermo-mechanical effects, leading to better lifespan. These converters, granular, are described and compared to the bulk converters generally used. Their characteristics concerning the yield and the thermal load are analyzed. Experiments carried out at KEK with such converters provided results which are also related. Such granular targets can also be used in conventional sources.

Application of diagnostic network optimization in Kenya and Nepal to design integrated, sustainable and efficient bacteriology and antimicrobial resistance surveillance networks.

Antimicrobial resistance (AMR) is a major global public health concern, particularly in low- and middle-income countries, which experience the highest burden of AMR. Critical to combatting AMR is ensuring there are effective, accessible diagnostic networks in place to diagnose, monitor and prevent AMR, but many low- and middle-income countries lack such networks. Consequently, there is substantial need for approaches that can inform the design of efficient AMR laboratory networks and sample referral systems in lower-resource countries. Diagnostic network optimization (DNO) is a geospatial network analytics approach to plan diagnostic networks and ensure greatest access to and coverage of services, while maximizing the overall efficiency of the system. In this intervention, DNO was applied to strengthen bacteriology and AMR surveillance network design in Kenya and Nepal for human and animal health, by informing linkages between health facilities and bacteriology testing services and sample referral routes between farms, health facilities and laboratories. Data collected from the target settings in each country were entered into the open-access DNO tool OptiDx, to generate baseline scenarios, which depicted the current state of AMR laboratory networks and sample referral systems in the countries. Subsequently, baselines were adjusted to evaluate changing factors such as samples flows, transport frequency, transport costs, and service distances. Country stakeholders then compared resulting future scenarios to identify the most feasible solution for their context. The DNO analyses enabled a wealth of insights that will facilitate strengthening of AMR laboratory and surveillance networks in both countries. Overall, the project highlights the benefits of using a data-driven approach for designing efficient diagnostic networks, to ensure better health resource allocation while maximizing the impact and equity of health interventions. Given the critical need to strengthen AMR laboratory and surveillance capacity, DNO should be considered an integral part of diagnostic strategic planning in the future.

Assessing the Effectiveness of the Tahfidz Program: A CIPP (Context, Input, Process, and Product) Model Evaluation Approach

This study aims to assess the implementation of the tahfidz program at Al Fawwaaz PPTQ Islamic Boarding School using the CIPP evaluation model. Employing a qualitative field research approach, the study involved the principal, deputy head of tahfidz, and tahfidz teacher as participants. Data collection techniques included observation, interviews, and documentation. Data analysis was conducted using the interactive model analysis technique proposed by Miles, Huberman, & Saldana (2014). The findings revealed that the tahfidz program aligns with student needs, community expectations, and institutional goals. Program planning is clear and purposeful. However, certain aspects require improvement, such as enhancing teacher proficiency in the classical tahsin system. The full tahfidz scholarship program initially targeted students with above-average memorization skills to complete 30 Juz Salama in three years. However, attracting students meeting these criteria proved challenging. Facilities and infrastructure are well-prepared, but specific facilities to accommodate students with auditory learning preferences are lacking. Process evaluation indicated that many students fall short of the set targets each semester, and nighttime memorization sessions are less effective. Additionally, some students prioritize fluency over proper makhraj and tajweed pronunciation. Product evaluation demonstrated positive outcomes, with memorization achievements aligning with individual student abilities. Overall, the tahfidz program at Al Fawwaaz PPTQ shows promise but requires ongoing evaluation and improvement to optimize its effectiveness.

Critical Success Factors For Quality Improvement Projects In Pasuruan, East Java, Indonesia

Purpose: This study aims to determine the factors influencing the successful implementation of quality improvement projects. Theoretical framework: This research will focus on finding critical success factors for quality improvement projects and prioritizing improvements to improve the performance and success of quality improvement project implementation. Design, Methodology and Approach: The research used Smart PLS-SEM and Importance Performance Analysis (IPA). Smart PLS-SEM was first used to determine critical success factors for Quality Improvement Projects (QIPs). Furthermore, IPA was used to determine the position of each factor based on its importance and achievements. Findings: The result showed all dimensions and indicators significantly affect the success of quality improvement projects. The dimension with the highest outer loading value is the quality performance measurement dimension. The next step is measured using the IPA method to determine the critical factors for project success. The results of the IPA analysis show that quality control and leadership are crucial factors in the success of quality improvement projects in the second quadrant. At the same time, the factor that prioritizes improvement is quality assurance (first quadrant). Research, Practical & Social implications: Research, Practical, and Social Implications: The research implies that quality control and leadership are critical success factors for quality improvement projects. Leadership plays an essential role in implementing quality improvement projects, and leadership commitment is an important key to the success of these projects. In addition, there is a requirement for support from leadership regarding resource allocation. This resource allocation includes labor, costs, information systems, machines, and tools. Another factor that is critical to the success of these projects is quality control. Implementation of quality control has a vital role during the quality improvement project process and after the project. With quality control, the product suits the specifications and standards and meets the targets and standards set. Products that track the results of the implementation of quality control can ensure that the product's quality is guaranteed and follows the target set. Originality/Value: This research combines two methods to determine the critical success factors in implementing quality improvement projects. Previous research, using SEM-PLS and IPA method measurements, was carried out separately, measuring the importance and performance levels. In this study, the outer loading results in the original sample measurement with SEM-PLS for importance value in the IPA method.