Importance Of Decision Criteria Research Articles

Development of an intraductal papillary mucinous neoplasm malignancy prediction scoring system.

Despite the presence of various guidelines, diagnosing malignant intraductal papillary mucinous neoplasm (IPMN) continues to pose challenges. Furthermore, although endoscopic ultrasonography (EUS) offers high-resolution images, it has not yet recognized as the primary tool for malignancy diagnosis. The study objective was to develop a simplified and user-friendly scoring system to improve the diagnostic accuracy of malignant IPMNs. Additionally, the utility of EUS and its effect on diagnostic accuracy were assessed. We retrospectively collected the clinical data on 160 cases of resected IPMN at Tokyo Medical and Dental University Hospital from January 2008 to December 2022. We examined clinical features, computed tomography (CT) and magnetic resonance imaging (MRI) findings, and EUS results if available. We then calculated the odds ratio of malignancy for these factors and developed an IPMN malignancy prediction (IMAP) scoring system. There were 89 (55.6%) cases of benign IPMNs and 71 (44.4%) of malignant IPMNs. Eight clinical and imaging findings, including age, diabetes mellitus status, jaundice, CA19-9 level, enhancing mural nodules ≥5mm, thickened wall, and main duct dilatation, were significantly associated with malignancy. The IMAP score was calculated by assigning 0 to 2 points to these factors based on the odds ratio. The area under the receiver operating characteristic curve for the IMAP score was 0.78 [95% confidence interval (CI): 0.71-0.85] based on CT/MRI alone and improved to 0.81 (95% CI: 0.74-0.87) when EUS was added. When the total exceeds 5 points, the positive predictive value becomes 100% (95% CI: 95.9-100). In conclusion, the IMAP scoring system has demonstrated promise as a clinically useful tool, offering both simplicity and sufficient accuracy. It holds potential as an important decision criterion for determining the treatment approach for IPMN. Additionally, EUS contributes to enhancing the diagnostic accuracy of the IMAP scoring system, thereby enabling more precise decision-making.

Environmental, economic and energy evaluation of alternative fuels for a steam power plant: Focus on biodiesel-nanoparticles utilization

Power plants are among the largest producers of GHGs. The fuel used in power plants is the main factor in the production of the emissions. Therefore, choosing a fuel that is environmentally optimal while being energy-efficient and economical is a key way to reduce GHG emissions. The addition of nanoparticles to biodiesel fuel not only improves the combustion efficiency of the fuel but also reduces the undesirable products. In this research, three supplementary fuels - fuel oil, diesel, and biodiesel-nanoparticles - are compared in terms of environmental, economic, and energy efficiency in a steam power plant. The changes in the power plant's self-consumption were measured by calculating the power consumption of the pump that delivers the fuel to the boiler. The results showed that diesel reduced the plant's efficiency by 0.00022 compared to using natural gas, which was the least of the other alternatives. The environmental analysis revealed that diesel produced the least amount of CO2 eq, but biodiesel-nanoparticle had a better CO2 footprint due to the higher absorption of CO2 in the cultivation phase of the raw material for biodiesel. The economic analysis for the fuels was carried out over ten years and based on the lifetime of the equipment purchased. Consequently, the total cost over the ten years for diesel was $967332.5161, which was $124475.8381 less than that for biodiesel-nanoparticle and $240935.3341 less than that for fuel oil. Finally, an overall comparison was made between the fuels using the AHP method. As the environmental criterion was the most important decision criterion, biodiesel-nanoparticle fuel was chosen with a marginal difference compared to diesel.

Impact of customer portrait information superiority on competitive pricing of EV fast-charging stations

The rapid development of electric vehicles (EVs) has increased the demand for public fast-charging stations (FCSs). Multiple self-interested charging service operators (CSOs) in an urban transportation network compete with each other through pricing signals to maximize their respective profits, where the information about customer demands and heterogeneous preferences work as important decision criteria. With the prevailing data transaction, the information superiority differences between CSOs may significantly affect the competitive pattern in the charging market. In this study, a Nash-Stackelberg-Nash game framework is established to investigate the strategic pricing of CSOs under different information distribution scenarios. The customer response pattern, namely, the routing and charging choices of EV drivers to pricing signals, is described via a computationally efficient extended stochastic user equilibrium model comprehensively considering heterogeneous customer preferences and decision stochasticity. Then, aiming at different data forms, both parameter-driven and sample-driven CSO pricing models are proposed. The pricing models are reformulated as a tractable single-level mixed-integer linear program, and the game equilibrium is solved alternately via Gauss-Seidel iteration. Numerical simulations are conducted to analyze the impact of single CSO information superiority and double CSO information distribution on CSO profitability and customer experience in both data forms. The influences of endogenous factors like CSO data amount and processing ability, as well as exogenous scenario parameters like customer preference distribution and perception error distribution, are discussed.

Metaheuristic for the integrated electric vehicle and crew scheduling problem

Encouraged by international efforts to reduce greenhouse gases and local emissions, many public transport operators are converting their fleets to battery-powered electric buses. Public transport operators can choose between different electric bus concepts, with the total cost of ownership being the most important decision criterion. The associated strategic decisions regarding charging strategy, vehicle concept, and charging infrastructure have a significant impact on the operational planning of the electric buses.Motivated by this, this paper aims to analyze the interactions between electrification and operational planning, especially vehicle scheduling and crew scheduling. This allows us to make a more comprehensive comparison of different electrification concepts. Prior work has addressed the impact of electrification on vehicle scheduling but has neglected the interactions with crew scheduling. Crew scheduling dominates operational costs and planning for many public transport operators and must therefore be considered in all strategic decisions. For this reason, in this work we focused on integrated electric vehicle and crew scheduling problem. This allows us to calculate the total cost of ownership of different electric bus concepts under better representation of local conditions. We deal with the electric vehicle and crew scheduling problem with a metaheuristic based on Adaptive Large Neighborhood Search. We tested the developed methodology for a real-world bus route. Our results indicate that the constraints for crew scheduling significantly impact the total cost of ownership and the required number of vehicles of the different electrification concepts. Our case study suggests that the choice of the most cost-effective concept depends significantly on crew scheduling constraints. These findings imply that crew scheduling constraints should be considered as part of the local framework for bus fleet electrification.

Management of orbital floor fractures in France: Results of a national online survey

IntroductionOrbital floor fractures (OFF) are common facial trauma injuries, and there are no official guidelines for their medical and surgical management. The aim of this study was to provide an overview of the management of OFF in France. Materials and methodsAn online questionnaire was sent to 144 surgeons at the 88 French centers involved in the management of OFF (2019 data from the National Health Insurance Body). The questions related to the preoperative clinical and radiographic examinations, the criteria for surgical indication, the materials used, and the elements of the postoperative period. ResultsUltimately, 42 questionnaires were analyzed (32 from oral and maxillofacial surgeons (OMFS), 8 from ophthalmologists, and 2 from ENT or plastic surgeons). For 69% of the surgeons, a systematic ophthalmological examination was carried out, 3–7 days after the trauma, and based on a Lancaster test or visual acuity (97.6% and 83.3% of the responders, respectively). The most important criteria for the therapeutic decision were diplopia or oculomotor disorder that persisted for more than 7 days (76.2%), clinical enophthalmos (54.8%), a large fracture (52.4%), and ptosis of the orbital content on CT scan (38.1%). The mean surgical delay was 7–15 days for 54.8% of the responders. Resorbing sheets were the preferred materials to repair small fractures, while larger fractures required alloplastic implants (titanium mesh). ConclusionThis survey confirms the diversity of practices in France regarding the management of OFF. Further studies are needed before guidelines can be developed.

Musculoskeletal simulation of elbow stability for common injury patterns.

Elbow stability is derived from a combination of muscular, ligamentous, and bony structures. After an elbow trauma the stability of the joint is an important decision criterion for the subsequent treatment. The decision regarding nonoperative/operative care depends mostly on subjective assessments of medical experts. Therefore, the aim of this study is to use musculoskeletal simulations as an objective assessment tool to investigate the extent to which failure of different stabilizers affects the elbow stability and how these observations correspond to the assessment from clinical practice. A musculoskeletal elbow simulation model was developed for this aim. To investigate the stability of the elbow, varus/valgus moments were applied under 0°, 45°, and 90° flexion while the respective cubital angle was analyzed. This was performed for nine different injury scenarios, which were also evaluated for stability by clinical experts. With the results, it can be determined by which injury pattern and under which flexion angle the elbow stability is impaired regarding varus/valgus moments. The scenario with a complete failure of the medial and lateral ligaments and a fracture of the radial head was identified as having the greatest instability. The study presented a numerical determination of elbow stability against varus/valgus moments regarding clinical injury patterns, as well as a comparison of the numerical outcome with experience gained in clinical practice. The numerical predictions agree well with the assessments of the clinical specialists. Thus, the results from musculoskeletal simulation can make an important contribution to a more objective assessment of the elbow stability.

Development of a Machine learning assessment method for renewable energy investment decision making

The aim of this study is to develop a hybrid methodology based on statistical approach and machine learning algorithm to structure the investment decisions in renewable energy industry. Six main criteria including GDP rate, inflation rate, electricity demand, electricity generation from Renewable Energy Technology (RET), electricity price, and CO2 emissions are used to classify and structure the decision-making algorithm. The risk related to each feature is calculated through using standard deviation of their historical data collected from each country. The Machine Learning (ML) algorithms such as Artificial Neural Network (ANN), Logistic regression (LR), Support Vector Machine (SVM), Decision Tree (DT), Naive Bayes (NB), k-Nearest Neighbors (k-NN), Random Forest (RF), and Ada Boost (AB) have been applied on the dataset related to each RET to classify the countries from the lowest risk (best country) to the highest risk (worst country) in terms of RET investment alternatives. LR, SVM, ANN, and DT showed the best performance among other ML algorithms. The highest accuracy was 0.94 and the lowest accuracy belonged to AB with the value of 0.24 for biomass technology. The minimum and maximum MSE was obtained 0.058 and 0.771 by LR for biomass technology and AB for hydropower technology, respectively. Moreover, the electricity generation risk from RET and electricity price risk in each country are the most important criteria for decision making in RET investment.

Branding in Sustainability

Purpose: A recent report published by Shelton Group, Sustainability(S) is rated for as an important brand purchase decision (P) criterion for 60 percent of consumers. The objective of this research is to investigate how differences affect consumers’ online and offline behaviors. 
 
 Design/methodology/approach: Through sentiment analysis of corporate website Brand Sustainability Strategies (BSS) is explored in the store level and in the social media platform level with a dedicated survey about S and the positive impact on their P.
 
 Findings: This study demonstrates how the millennials generation experience through virtual interaction (VI) leverage on P and improve the Customer Brand Experience (CBE), focuses on Lego and Adidas 
 
 Originality/value: The paper contributes to study a topic more interesting in this period and in addition underlines the culture emerged among the online and the offline P in the relation with the strategies of the customer journey.

Presentation of ethical criteria during medical decision-making for critically ill patients: a mixed methods study.

Every medical decision is based on balancing medical knowledge, ethical considerations, and patient preferences. Previous surveys have mainly covered the ethical knowledge of medical staff. The aim of this study is to evaluate the feasibility of an innovative concept regarding how ethical criteria are applied to clinical decision-making during critical illness. An online survey including a short case vignette was carried out at a university hospital among physicians specialising in intensive care medicine in Germany. After free text responses regarding further required case information, the participants were asked to rank decision criteria during the course of the case vignette. A qualitative evaluation was performed by two independent investigators, based on a transcription into categories. This was followed by a quantitative analysis of ranked criteria. Our analysis has shown that doctors are initially inclined to consider medical information when making treatment decisions. When complications occur, ethical values are more often included in the decision-making. The qualitative evaluation reveiled that the patient's will was consistently regarded as the leading criterion for decision-making. In the quantitative evaluation, patient's well-being, quality of life, and patient autonomy were rated as the most important decision criteria. Economic factors were ranked least important. A mixed methods approach is able to reflect the complexity of ethical reasoning within the medical decision-making process, suggesting the feasibility of this concept. The study was registered under DRKS-ID: DKRS00011905 (April 2017).

Origin of the Cretaceous olistostromes in the Oman mountains (Sultanate of Oman): Evidence from clay minerals

Mid- to Late Cretaceous olistostrome generation ensued sequentially, linked to progressive southwest-directed thrusting of the Semail Ophiolite towards and over Arabia – at first in the northeastern part of the oceanic Hawasina Basin (Umar Sub-Basin) and then in its southwestern part (Hamrat Duru-Sub-Basin). Thrusting steepened slopes, causing seismic tremors, which destabilized slope sediments and triggering olistostrome formation. Ophiolite thrusting over Arabia created the Aruma Foreland Basin. Olistostrome formation in the foredeep ensued last and on the flank of the uplifting forebulge.As olistoliths, Olistostrome 1 contains radiolarian limestone, plain micrite, allodapic limestone, basalt, amygdaloidal basalt, radiolarian chert and coarse, massive limestone with crystalline texture (Oman Exotics). These olistoliths “float” in shale, containing illite/muscovite, vermiculite and kaolinite. Olistostrome 1 formed in the Umar Sub-Basin.Olistostrome 2 is associated with the Late Albian to Coniacian Nayid Formation of the Hamrat Duru Sub-Basin. It is characterized by olistoliths of graded limestones (calc-turbidites) with angular shelfal limestone lithoclasts. The olistoliths are embedded in shale with unidentifiable clay minerals. Olistostrome 2 formed in the Hamrat Duru Sub-Basin, postdating Olistostrome 1.Olistostrome 3 is associated with the Upper Cretaceous Aruma Foreland Basin and characterized by olistoliths, like lithoclastic packstone (calcarenite), dolomitic limestone, and sandstone with carbonate lithoclasts. The matrix of the olistoliths is a pyrophyllite- and kaolinite-bearing shale. Olistostrome 3 formed in the foredeep as the youngest olistostrome.The different clay mineralogy of Olistostrome 1 and Olistostrome 3, reflects their different basinal origin. Shale samples taken from conventional sediments (no olistostromes) of the syn-tectonic and post-tectonic Aruma units show some resemblance in their clay mineralogy as they contain detritus from the Oman Mountains. Olistolith types of both Hawasina olistostromes differ significantly.The reviewed and novel data may serve as a guideline for future olistostrome studies in the Oman Mountains and may be particularly helpful in identifying the basinal origin of olistostromes in case of fault-bounded olistostromes, unexposed olistostrome contacts and inconclusive olistoliths. Evaluating matrix shales of olistostromes leads to important decision criteria, such as color, oxygenation state and clay mineralogy, to determine the paleogeographic basin position.

Offshore wind power plant site selection using Analytical Hierarchy Process for Northwest Turkey

This study presents a quantitative methodology for offshore wind power plant site selection in Northwest Turkey using Geographical Information Systems (GIS) and Analytical Hierarchy Process, which is one of the Multi-Criteria Decision Making methods. A comprehensive literature review is conducted to identify more than 17 site selection criteria and required GIS data were collected accordingly. Site selection criteria are classified as decision and exclusion criteria. Decision criteria along with their suitable limits and exclusion criteria are evaluated in GIS resulting in five alternative suitable sites. Alternative site pairwise comparison matrices are formed in terms of each decision criterion. In the meantime, a hierarchy of decision criteria is formed, and a questionnaire comparing the relative importance of decision criteria is conducted on national and international experts. Electricity grid connection, offshore average wind speed at 100 m height and environmental concerns are found to be the most important decision criteria. Relative importance of decision criteria and alternative site comparisons are combined in two different analyses, namely “scenario analysis” and “consensus analysis”. Out of the five alternative sites, Bozcaada is concluded to be the most suitable site, and the second-best alternative is Kıyıköy.

Comparative Study between Operative and Conservative Management of Penetrating Anterior Abdominal Stab Injuries

Background: Presently, non-operative management of penetrating abdominal stab injuries has been standardized in several trauma centers. This strategy has appromising outcome conserving decreasing morbidity.
 Aim of the work: This study aimed to assess the safety and feasibility of SNOM of patients having penetrating abdominal stab injuries not indicating emergent laparotomy and to identify a protocol for selection of patient candidates for non-operative management in a tertiary care hospital in Egypt.
 Patients & Methods: This is a prospective study that involved patients who presented to the casualty department of Kasr Elainy teaching Hospital, in the period from August 2018 to August 2020, for management of a penetrating abdominal Stab injuries. Fully conscious, haemodynimacally stable patients were included. Eligible patients were allocated to either SNOM group or immediate operative management (IOM) group.
 Results: SNOM group included64 patients and IOM group included 40 patients. The age of the patients ranged from 16 to 49 years with a mean of 33±6.8 years, and the majority were males (99%). SNOM failed in 4/69 patients (5.7%) who required delayed laparotomy for peritonitis (2 cases) and HB drop and haemodynamic instability (2 cases). In IOM group, only 3 cases had therapeutic laparotomies (7.3%). The remaining cases had unnecessary laparotomies (92.7%). Statistically significant higher LOS was seen in SNOM group (p<0.05). However, less unnecessary laparotomies and lower incidences of complications were noted (p<0.01).
 Conclusion: vital signs together with abdominal examination are the most important clinical criteria in decision making in penetrating abdominal stab injury patients When surgery is not absolutely indicated, SNOM is a safe and feasible approach in management of penetrating abdominal stab injury by following proper management algorithm and selection criteria.

Deciding on inventory allocation policies in the auto parts Brazilian distribution chain

The purpose of this paper is to evaluate the decision regarding whether to centralise or decentralise the stock of auto parts in Brazilian context. Extensive research was conducted regarding stock allocation policies, with a focus on centralisation and decentralisation, whereas the criteria for this decision were actually validated according to the opinion of Brazilian dealerships. A survey of 119 dealers revealed the important criteria for decision making using the analytic hierarchy process (AHP) approach. Our results demonstrate that dealerships assign high importance to delivery lead time, quality and flexibility in the delivery process from automakers. The results reveal that the simple trade-off between service level and inventory cost does not offer a definite distribution net design regarding stock allocation policies. This paper contributes by showing the criteria related to different types of stock allocations influence the decision regarding whether to centralise an auto parts' distribution chain in Brazil.

Adoption of Precision Technologies by Brazilian Dairy Farms: The Farmer's Perception.

Simple SummaryUnderstanding the perception of dairy farmers regarding precision livestock technologies is crucial for creating strategic actions that will increase the rate of adoption and usage of such technologies. A survey study was applied to 378 dairy farms located in Brazil. The farmers were characterized based on technology usage, farmer profile, farm characteristics, and production indexes. The farms were classified into seven clusters: (1) top yield farms; (2) medium–high yield, medium-tech; (3) medium yield and top high-tech; (4) medium yield and medium-tech (5); young medium–low yield and low-tech; (6) elderly medium–low yield and low-tech; and (7) low-tech grazing. Our study helped to elucidate the farmer’s perception about precision technologies and to shed light on challenges that need to be addressed by scientific research and extension programs.The use of precision farming technologies, such as milking robots, automated calf feeders, wearable sensors, and others, has significantly increased in dairy operations over the last few years. The growing interest in farming technologies to reduce labor, maximize productivity, and increase profitability is becoming noticeable in several countries, including Brazil. Information regarding technology adoption, perception, and effectiveness in dairy farms could shed light on challenges that need to be addressed by scientific research and extension programs. The objective of this study was to characterize Brazilian dairy farms based on technology usage. Factors such as willingness to invest in precision technologies, adoption of sensor systems, farmer profile, farm characteristics, and production indexes were investigated in 378 dairy farms located in Brazil. A survey with 22 questions was developed and distributed via Google Forms from July 2018 to July 2020. The farms were then classified into seven clusters: (1) top yield farms; (2) medium–high yield, medium-tech; (3) medium yield and top high-tech; (4) medium yield and medium-tech; (5) young medium–low yield and low-tech; (6) elderly medium–low yield and low-tech; and (7) low-tech grazing. The most frequent technologies adopted by producers were milk meters systems (31.7%), milking parlor smart gate (14.5%), sensor systems to detect mastitis (8.4%), cow activity meter (7.1%), and body temperature (7.9%). Based on a scale containing numerical values (1–5), producers indicated “available technical support” (mean; σ2) (4.55; 0.80) as the most important decision criterion involved in adopting technology, followed by “return on investment—ROI” (4.48; 0.80), “user-friendliness” (4.39; 0.88), “upfront investment cost” (4.36; 0.81), and “compatibility with farm management software” (4.2; 1.02). The most important factors precluding investment in precision dairy technologies were the need for investment in other sectors of the farm (36%), the uncertainty of ROI (24%), and lack of integration with other farm systems and software (11%). Farmers indicated that the most useful technologies were automatic milk meters systems (mean; σ2) (4.05; 1.66), sensor systems for mastitis detection (4.00; 1.57), automatic feeding systems (3.50; 2.05), cow activity meter (3.45; 1.95), and in-line milk analyzers (3.45; 1.95). Overall, the concerns related to data integration, ROI, and user-friendliness of technologies are similar to those of dairy farms located in other countries. Increasing available technical support for sensing technology can have a positive impact on technology adoption.

Wie wählen internistische Patienten ihr Krankenhaus? Eine Querschnittstudie

ZusammenfassungEinleitung Die freie Krankenhauswahl durch Patienten wird gesundheitspolitisch gefördert und soll durch die Qualitätsberichte der Krankenhäuser unterstützt werden. Doch wie entscheiden sich Patienten für ein Krankenhaus? Wie viele können selber entscheiden, wo informieren sie sich und was sind in der konkreten Situation ihre Entscheidungskriterien? Dies soll für stationäre Patienten der Inneren Medizin im Vergleich zu denen anderer Fachgebiete beantwortet werden. Methoden Die Daten entstammen einer Beobachtungsstudie. Die nach Fachgebieten und Krankenhausversorgungsstufen geschichtete Zufallsstichprobe wurde in 46 Fachabteilungen von 17 Krankenhäusern aus 15 Städten und Gemeinden Nordrhein-Westfalens erhoben. Die gewichtete Stichprobe wertet 758 Patienten der Inneren Medizin und 1168 Patienten anderer Fachgebiete deskriptiv und inferenzstatistisch aus. Ergebnisse Internistische Patienten sind älter, häufiger Männer, ohne Migrationshintergrund und chronisch krank, zudem öfter stationär vorbehandelt. Etwa die Hälfte entscheidet selbst über das Krankenhaus, wobei die eigene Kenntnis des Krankenhauses durch einen Voraufenthalt die wichtigste Informationsquelle darstellt und wichtige Entscheidungskriterien die eigene Vorerfahrung, der Ruf des Krankenhauses und die Empfehlung der ambulanten Behandler sind. Der kleine Anteil Patienten mit mehr Zeit vor der Aufnahme wählt das Krankenhaus aktiver. Diskussion In der Inneren Medizin können weniger Patienten selbst über das Krankenhaus bestimmen. Diese entscheiden dann überwiegend aufgrund ihrer Vorerfahrung mit dem Krankenhaus und setzen die erneute Behandlung im ihnen bekannten Krankenhaus, in dem auch sie bekannt sind, fort. Ein kleiner Anteil jüngerer, gebildeterer und weniger krankenhauserfahrener Patienten informiert sich aktiver vor elektiven Eingriffen. Die Behandlungserfahrungen der Patienten sind zentral bei der eigenen Krankenhauswahl und über den sozialen Austausch auch bei der ihrer Angehörigen.

How do Surgical Patients Choose their Hospital? A Cross-sectional Study

Free hospital choice is promoted in health policy through public quality reporting. Previous studies on hospital choice mostly survey patients for specific elective procedures. This study examines all full inpatient surgical patients and compares them to those in other specialties. Research questions are: How many patients make their own decisions about the hospital? How much time do they have before admission? Where do they obtain information and what are their important decision criteria? This study evaluates cross-sectional primary data on hospital choice collected by questionnaire from 1925 consecutively hospitalised patients from 11 medical specialties and 3 levels of care, including 438 surgical patients from 6 general surgery departments. Three quarters of surgical patients decide on the hospital themselves. Their own previous experience with the hospital is an important source of information and decision-making criterion for a good half of the patients, along with relatives and outpatient treatment providers as well as the hospital reputation. Many surgical patients decide in favour of a hospital because of the trust they have built up through previous treatment in the hospital, which they experience as satisfactory. The professional quality of treatment is thus the greatest impact factor on patients, their relatives and outpatient treatment providers. It is important to actively and specifically address and clarify possible dissatisfaction on the part of the patient before discharge.

Narrative Review of Tracheostomy Procedure during COVID-19 Pandemic

The COVID-19 pandemic has led to an unprecedented increase in the number of critically ill patients requiring mechanical ventilation. Tracheostomy played an important role to wean off the patients from ventilator support and maximize the resources. Tracheostomy is an aerosol generating procedure (AGP) which raised some controversial issues as it carries a risk of infection to healthcare workers. This study aims to review the issues related to tracheostomy procedure in COVID-19 patients, including the appropriate time to perform tracheostomy, criteria for patient selection, safer approach and risk of infection among healthcare workers. Related information retrieved via online search of original articles, paper reviews, recommendations and guidelines from PubMed, Medline and Google Scholar using keywords tracheostomy, COVID-19, intensive care and mechanical ventilation are summarized in this article. The suggested time frame to perform tracheostomy ranged from 7 to 21 days. Early tracheostomy performed between day 10 to 14 had beneficial outcome for the patients and helped to reduce ICU occupancy. Decision for appropriate timing was made after considering the viral load and the course of the disease. Criteria for patient selection based on suggestions from studies and guidelines were lower oxygen requirement (FiO2<0.4, PEEP< 10), low Sepsis Related Organ Failure (SOFA) scores, ventilation for at least 10 days and signs of improvement. Patient factors, availability of facilities and expertise were important criteria for decision to undertake tracheostomy. The patient outcomes from tracheostomy varied between centers. Most of the studies reported that none of the healthcare workers had been infected by utilizing appropriate PPE and by taking important precautions during the procedure. In conclusion, guidelines were established for tracheostomy procedure during COVID-19 but the decision to undertake the procedure still depend on a case by case basis.

Analysis of the consumer preferences of attributes of Rajini Modest Fashion Products

The market growth of modest fashion products is increasing. Rajini uses this opportunity by developing modest fashion products. The purpose of this study was to discover and analyze which attributes most affect the purchase of modest fashion products by consumers. The results were used by Rajini to be more effective in developing modest fashion products. The study was conducted with 100 respondents using purposive sampling. Data collected were analyzed using conjoint analysis with the SPSS 25 programs. The preferred attributes in choosing modest fashion products included “neutral color”, “classic style”, “lightweight fabric” and “normal fit”. The most important decision criterion when purchasing modest fashion products was the aesthetic attribute “style”, followed by “color”, and then the functional attribute “fit”. The “fabric” attribute was perceived as least important. In order to better compete, Rajini needs to adjust consumer preferences in Surabaya according to the results of this study.
 Keywords: modest fashion, consumer preferences, conjoint analysis, color, style, fabric, fit

Strengthening urban sustainability: Identification and analysis of proactive measures to combat blight

The process of identifying and analyzing proactive measures for the prevention of urban blight is complicated by its complexity and death of data. Blight affects people’s lives in many ways, including economically, socially, psychologically, and physically. The phenomenon comprises many factors, including making appropriate identification and eradication decisions that are challenging to analyze and structure. This study took a constructivist stance and sought to develop a new approach to urban blight to complement the existing literature. The methodology combined cognitive mapping techniques applied in decision conferences, and the decision making trial and evaluation laboratory technique based on the multiple-criteria decision analysis approach. This integrated approach facilitated the development of a multi-criteria model that identifies proactive anti-blight measures in a more complete, transparent way. This dual methodology enables incorporating objective and subjective elements, and field specialists’ knowledge and experiences, thereby reducing important decision criteria omissions. Additionally, this approach generates a transparent visualization of relationships among criteria. Identified blight determinants can be used to prevent blight, and improve the quality of life in the affected areas. These strategies were carefully analyzed by two independent experts from the Direção Geral do Território (General Directorate of the Territory of Portugal). The advantages and limitations of the proposed methodology are also deliberated. • This real-world study contributes to a holistic understanding of urban blight. • The process-oriented approach followed overcomes some limitations of purely statistical methods. • Cognitive mapping and DEMATEL improve the understanding of proactive anti-blight strategies. • No prior research was found that has adopted the proposed methodology in this study context.

Insights about the Choice of Pig Manure Processing System in Three Italian Regions: Piemonte, Friuli Venezia Giulia, and Veneto

The adoption of best available technologies (BATs) by the livestock sector has a fundamental role in developing a sustainable agricultural system. Italy is the EU member with the highest percentage of manure treated, but processing facilities are regionally scattered and the adoption of BATs is far from being scaled-up. The adoption is a matter of multicriteria decision-making and full knowledge on how to foster the transition is still lacking. The present research aims to deepen the available knowledge by analysing the perception of 40 pig farm managers about decision criteria behind the adopted manure management system across three different Italian regions. We assessed farms in Piemonte, Friuli Venezia Giulia, and Veneto. All farms have adequate storage facilities, but 82.5% adopt no processing technique. The two most important decision criteria are economic, i.e., the minimization of treatment and spreading costs. The emerging picture allows us to conclude that BAT adoption is still adopted as a mere consequence of legal obligation. Economic constraints prevail as there is a lack of information and uncertainty. Clear perspectives and recognition of virtuous behavior prevent farmers from making decisions based on environmental or social criteria. Therefore, effective policies oriented to fill these gaps are needed to accelerate the transition towards sustainability.