Output Levels Research Articles

Strategic alliances and partnerships based on the semi-additive production technology in DEA

Strategic alliances and partnerships based on mergers and acquisitions can be used to improve the performance of decision-making units (DMUs). In this paper, we present different types of strategic alliance cooperation and partnership between DMUs and their corresponding aggregation DMUs. We propose two different strategies, we were able to carry out the process of strategic alliances and partnerships in semi-additive production technology. In the first strategy, two partner DMUs can compensate for the lack of resources in some of their input components by using excess input resources in some of each other's input components. Thus these DMUs can improve their efficiency score among all DMUs. The modeling of strategic alliances and partnerships in the first strategy was based on data envelopment analysis (DEA) models. In the second strategy, the two DMUs selected as partners adjust their input and output levels with the help of each other in such a way that these two DMUs achieve a target efficiency level predetermined by the DM. The modeling of strategic alliances and partnerships in the second strategy was based on inverse DEA models. We also apply the proposed approach to show importance strategic alliances and partnerships in banking. In the following, we compared the results of the models in carrying out the partnership process in two different technologies. The results showed that in semi-additive production technology, we can achieve potential gains for banks.

Interval training has more negative effects on sleep in adolescent speed skaters: a randomized cross controlled trial.

Sleep is an essential component of athletic performance and recovery. This study aimed to investigate the effects of different types of high-intensity exercise on sleep parameters in adolescent speed skaters. Eighteen male adolescent speed skaters underwent aerobic capacity testing, Wingate testing, and interval training in a randomized crossover design to assess strength output, heart rate, and blood lactate levels during exercise. Sleep quality after each type of exercise was evaluated using the Firstbeat Bodyguard 3 monitor. The results showed that Wingate testing and interval training led to decreased sleep duration, increased duration of stress, decreased RMSSD, and increased LF/HF ratio (p < 0.01). Conversely, aerobic capacity testing did not significantly affect sleep (p > 0.05). The impact of interval training on sleep parameters was more significant compared to aerobic capacity testing (p < 0.01) and Wingate testing (p < 0.01). High-intensity anaerobic exercise has a profound impact on athletes' sleep, primarily resulting in decreased sleep duration, increased stress duration, decreased RMSSD, and increased LF/HF ratio.

인공지능 마젠타스튜디오(Magenta Studio)를 활용한 중등 블렌디드 러닝 창작 음악 교수학습 방안

Objectives The purposes of this study is a music class for middle school students using magenta, and artificial in-telligence(AI) creation program.&#x0D; Methods To this end, the structure, operating principles, and usage method of the Magenta were introduced. Next, a model for teaching Magenta online and offline was presented by applying blended learning teaching- learning.&#x0D; Results Using artificial intelligence in creative music classes can raise the level of musical output. Teachers and students can discover musicality by interacting online and offline.&#x0D; Conclusions This study can overcome limitations that my arise in the implementation of music creation classes. Also, using artificial intelligence can be effective difficult to use real instruments in the situation.&#x0D;

Analysis of factors influencing market participation among orange‐fleshed sweet potato smallholder farmers in southern region of Malawi: A case of RTC project

AbstractAgricultural markets remain major issue downgrading root and tuber crop farmers who form the mainstream of the agricultural producers in Malawi. Recent evidence however reveals that orange‐fleshed sweet potato (OFSP) (Ipomea batatas) is currently being sold in produce markets along with the non‐orange varieties, sometimes in differentiated form in Malawi. The main objective of this study was to examine factors affecting market participation of sweet potato farmers in southern region of Malawi. Using a double‐hurdle model, this paper analyzed both the factors affecting farmer decision to participate and the extent/intensity of participation in market. The first tier of the double hurdle focused on decision to participate in the market using probit model and the second tier addressed factors affecting intensity of participation using truncated normal regression model. The paper used data collected from 360 farmers in southern districts of Malawi. Out of 360, 146 farmers had grown OFSP in the season preceding the survey. Double hurdle results indicate that farm size, output, age of a farmer (household head), and early maturing trait significantly determined decision to participate in the market. Further, results on intensity of participation indicate that access to market training, farm size, asset value, and output positively determined the intensity and negatively determined by distance to main market and gender of a farmer (household head). Based on the research findings, higher output levels and early maturing trait were found to increase smallholder farmer market participation. It is therefore recommended that strategies aimed at increasing household capacity to produce surplus produce through market tailored extension messages and productivity enhancement technologies could be highly effective in fostering smallholders' participation in commercial markets. Again, enhanced capacity building of research institutions to breed sweet potato varieties based on market demand is pivotal for increased market participation. Furthermore, research suggests that improving smallholder farmers' access to market price information, asset value, and farm size can help increase their intensity in the market. Therefore, it is critical for policymakers to holistically comprehend these socioeconomic factors in order to address the issue of smallholder farm households' decisions about market participation and the degree to which they participate.

MA-MIL: Sampling point-level abnormal ECG location method via weakly supervised learning

Background and ObjectiveCurrent automatic electrocardiogram (ECG) diagnostic systems could provide classification outcomes but often lack explanations for these results. This limitation hampers their application in clinical diagnoses. Previous supervised learning could not highlight abnormal segmentation output accurately enough for clinical application without manual labeling of large ECG datasets. MethodIn this study, we present a multi-instance learning framework called MA-MIL, which has designed a multi-layer and multi-instance structure that is aggregated step by step at different scales. We evaluated our method using the public MIT-BIH dataset and our private dataset. ResultsThe results show that our model performed well in both ECG classification output and heartbeat level, sub-heartbeat level abnormal segment detection, with accuracy and F1 scores of 0.987 and 0.986 for ECG classification and 0.968 and 0.949 for heartbeat level abnormal detection, respectively. Compared to visualization methods, the IoU values of MA-MIL improved by at least 17 % and at most 31 % across all categories. ConclusionsMA-MIL could accurately locate the abnormal ECG segment, offering more trustworthy results for clinical application.

Impedance spectroscopy analysis of thermoelectric modules under actual energy harvesting operating conditions and a small temperature difference

Thermoelectric (TE) devices can convert heat into electricity and have gained great interest as energy harvesters in many applications, such as self-powered sensors, solar TE generators and industrial waste heat recovery. Not many techniques are usually available for their characterization under operating conditions. Consequently, only current-voltage (power output) curves are typically reported to account for their performance, which provide limited information. Impedance spectroscopy, which has been mainly applied to the study of TE modules suspended in air or vacuum, has the advantage to be used under operating conditions. Here, we exploit this advantage and provide an in-depth analysis of the impedance response of standard TE devices when they operate under a small temperature difference. First, we derive the physical models (equivalent circuits) for the two most common operating conditions: (i) constant temperature difference and (ii) constant heat power input. Then, we use the obtained equivalent circuit to successfully fit experimental impedance measurements in both operating modes, which show significant differences. From the fittings, it is possible to obtain the thermal contact resistance between the TE device and the heat exchangers (heat source and heat sink) among other key parameters. In addition, we analyze the variations found in the impedance spectra for different current output levels. Moreover, we show how different electrical resistances, extracted from the impedance results, directly relate to the slope of the I-V curve (power output), and can provide very valuable information about the different processes that determine its value. All these results establish impedance spectroscopy as a very powerful tool to characterize TE devices under operating conditions and as a method that can provide highly valuable insights into their performance.

Efektivitas Serapan Jagung Lokal Oleh Pabrik Pakan di Indonesia

The uptake of local corn by feed factories nationally in corn production and demand between regions is uneven, which creates corn shortages, so information services are needed for business actors. This research aims to analyze the effectiveness of local corn uptake by feed factories nationally using descriptive qualitative methods. The results of the research show that the local corn uptake information service in the Sijagung application from the five dimensions of Campbell's service effectiveness, namely service success, target success, satisfaction with service, level of input and output and achievement of overall goals is considered less effective because there is no updated data information, does not provide information projection data as corn absorption data required by feed factories nationally. To achieve the effectiveness of corn uptake information services by feed factories through the Sijagung application, it needs to be strengthened with a service integration dimension used to measure the extent to which the presentation of local corn uptake data nationally can be integrated with harvest condition data so that it can display projection data for Business Actors in making decisions to carry out purchase.

Assessing technical efficiency and its determinants for dairy cattle farms in northern Algeria: The two-step DEA-Tobit approach

The purpose of this paper is to analyze the technical efficiency of dairy cattle farms in Tizi Ouzou region as one of the main dairy basins in Algeria. To do so, a two-step analysis was applied. First, Data Envelopment Analysis (DEA) was used to quantify the technical efficiency of dairy cattle farms. In the second step, a Tobit model to examine factors affecting farms’ technical efficiency is used. The analysis used cross-sectional data collected from 146 dairy cattle farmers. The study found that the average technical efficiency under VRS assumption is relatively high, suggesting that farms can reduce their inputs by an average of 17% while maintaining the same level of output. The study also highlights the crucial role that agricultural advisory system and traditional insemination play in enhancing technical efficiency. In this region, where cattle breeding is traditionally practiced on a small scale, increasing herd size can result in reduced performance. The study also recommended that agricultural policies should be adapted to local specificities and that a more supportive strategy should be adopted for small-scale family dairy farms instead of promoting the large farm model.

In-Depth Assessment of Key Factors Affecting Coffee Production in Tanzania

Coffee has been among the traditional cash crops and one of the main contributors to foreign earnings in Tanzania. Consequently, earnings from its exports have remained low due to various production challenges which in turn affects export growth. These challenges have never been properly and intensively recognized for better decision-making. Therefore, this study was set to provide an in-depth assessment and understanding of key factors affecting coffee production in Tanzania.The study used simple random sampling to collect information from 364 respondents in four highly coffee-growing districts in Ruvuma, Mbeya, and Songwe regions. Qualitative and quantitative data were collected through structured questionnaires from small-scale farmers. Data were then analyzed by using a statistical Package for Social Sciences (SPSS) and Excel. From the findings, poor agronomic practices such as inadequate application of fertilizer, poor pesticides and disease control, and aged low-yield coffee trees were found to be the main factors that strongly explain the relationship with low coffee production output due to their significant results. Furthermore, using regression the other variables found to significantly affect coffee production output level were limited access to finance and inadequate extension services. Based on the findings, sustainability of the coffee sector development, intensive government intervention is needed by putting more priority on training farmers best agronomic practices in the right way. This way, small farmers can be aware of the importance of the application of required agronomic practices as a key factor in the scale-up of productivity and production output. The Bank of Tanzania can also efficiently address the challenge of small-scale farmers in obtaining soft loans at a reasonable cost from financial institutions by creating an enabling environment. This should include the provision of a special loan facility to commercial banks connected with conditions to beneficial banks to lend to farmers at an indicative rate that can be affordable to small-scale coffee growers. These findings will inform policymakers and coffee stakeholders in the coffee value chain on the best actions and decision-making to enhance the sector&amp;apos;s performance.

Solar desalination evaporator made of black round plastic lunch box and black garbage bag

So far, it is generally believed that black matter means that it can strongly absorb nearly 57 % of the energy in the incoming light of the sun. In the field of photothermal interface evaporation, there are many substances which surface is black but not concerned. Inspired by the above understanding, this paper selects disposable black round plastic lunch boxes and black garbage bags as solar absorption materials to make photothermal desalination evaporators for the first time, to prove that these black disposable wastes can not only be recycled, but also can be used to make interfacial evaporators. Polyester cloth is used as the water delivery channel, and the two-dimensional evaporation device made of black round plastic lunch box successfully achieves a high level of steam output. The value even exceeds 1.45 kg m-2 h-1. In addition, we also prepared a three-dimensional evaporator using a black garbage plastic bag as only solar energy absorber. The three-dimensional evaporator uses radiation cooling film as diffuse reflection substrate. The radiation cooling film and polyester cloth can multiple reflect and absorb the incident solar energy, so that the black plastic bag can multiple re-absorb the incident solar light. The solar energy absorption rate of the three-dimensional evaporator is as high as 95.14 %, and the steam output is as high as 8.91 kg m-2h-1.

Predictive Factors of Successful Double J Stent Insertion Among Advanced Cervical Cancer Patients.

Cervical cancer remains the most lethal and prevalent cancer among women. Obstructive uropathy is a common complication of advanced cervical cancer, caused by the expanding tumor. One of the recommended treatments for this condition is the implantation of a double J (DJ) stent. However, this procedure is challenging due to the unique characteristics of the patient. The objective of this study was to identify the variables that influence the successful insertion of a DJ stent in women with advanced cervical cancer. This retrospective study included women who attempted to have a DJ stent implanted at the General Hospital of Adam Malik in Medan, Indonesia, between January 2020 and December 2022, and were diagnosed with advanced cervical cancer. The inclusion criteria were limited to cervical cancer patients in stages III-IV, according to the International Federation of Gynecology and Obstetrics (FIGO) staging standard, who underwent an attempt at DJ stent insertion. Patients who underwent a nephrostomy and received a DJ stent were excluded from the study. The participants were divided into two groups based on the success of the DJ stent implantation. The analysis was conducted using the logistic regression test and the Chi-square test. The study included 88 patients with advanced-stage cervical cancer, of whom 45 underwent nephrostomy and 43 received a DJ stent. The analysis revealed that lower levels of hydronephrosis (odds ratio (OR): 18.203, P = 0.001), urea (OR: 4.207, P = 0.037), and creatinine (OR: 6.923, P = 0.004), higher levels of urine output (OR: 8.26, P = 0.003), and lower cervical cancer stage (OR: 4.125, P = 0.022) were all predictors of successful DJ stent insertion. For women with advanced cervical cancer, lower degrees of hydronephrosis, urea, and creatinine levels, higher urine output, and lower cervical cancer stage were all predictive factors for successful DJ stent implantation.

Optimization of piezoelectric device with both mechanical and electrical properties for power supply of road sensors

Collecting and converting renewable energy from the road environment relieves pressure on energy supply for road-based sensing and monitoring, and simplify the process of road grid installation. Aiming at the characteristic of mechanical vibration energy collection, the internal structure of the piezoelectric device is optimized. The dowel bar structure is optimized by comparing the output power and stress distribution characteristics, while the actuation mode is selected based on the measured electrical output level and output stability. Then, based on the limit distance of single and dynamic loading, the range of actuation distance under different conditions is clarified. Finally, the electrical performance and application of energy harvester with optimized internal structure are systematically evaluated. The results indicate that the force-electric properties of the energy harvester are superior under the action of the cylinder, the actuation mode of the energy harvester driven by the dowel bar is conducive to improving the electrical performance. The upper limit of actuation distance under high traffic conditions is 1.3 mm. Under long-term high-frequency condition, the power density of the energy harvester can reach 14,726.67 W/m3, and the voltage has almost no attenuation after 100,000 continuous loads. The proposed internal structure improves the electrical performance and durability of the energy harvester, which is conducive to the development of self-powered energy supply for road sensing technology.

Assessing the Efficacy of Large Language Models in Health Literacy: A Comprehensive Cross-Sectional Study.

Enhanced health literacy in children has been empirically linked to better health outcomes over the long term; however, few interventions have been shown to improve health literacy. In this context, we investigate whether large language models (LLMs) can serve as a medium to improve health literacy in children. We tested pediatric conditions using 26 different prompts in ChatGPT-3.5, ChatGPT-4, Microsoft Bing, and Google Bard (now known as Google Gemini). The primary outcome measurement was the reading grade level (RGL) of output as assessed by Gunning Fog, Flesch-Kincaid Grade Level, Automated Readability Index, and Coleman-Liau indices. Word counts were also assessed. Across all models, output for basic prompts such as "Explain" and "What is (are)," were at, or exceeded, the tenth-grade RGL. When prompts were specified to explain conditions from the first- to twelfth-grade level, we found that LLMs had varying abilities to tailor responses based on grade level. ChatGPT-3.5 provided responses that ranged from the seventh-grade to college freshmen RGL while ChatGPT-4 outputted responses from the tenth-grade to the college senior RGL. Microsoft Bing provided responses from the ninth- to eleventh-grade RGL while Google Bard provided responses from the seventh- to tenth-grade RGL. LLMs face challenges in crafting outputs below a sixth-grade RGL. However, their capability to modify outputs above this threshold, provides a potential mechanism for adolescents to explore, understand, and engage with information regarding their health conditions, spanning from simple to complex terms. Future studies are needed to verify the accuracy and efficacy of these tools.

Modifying the success story of Sweden: Revised output and labour productivity figures for manufacturing, 1869–1950

AbstractThe rampant growth rate of output and productivity in manufacturing borne out by Swedish Historical National Accounts (HNA) has nurtured the notion that the Swedish rise to prosperity was propelled by the confluence of disproportionately high levels of sophistication and very low levels of output per worker. The thrust of the argument is that this unique configuration allowed Sweden to leapfrog into modernization. The time has come to put this arresting claim under scrutiny, which is the foremost aim of this paper. This claim, we argue, is founded on a questionable empirical foundation. The most frequently used series of outputs from manufacturing at large and from groups of industries are those of the Swedish HNA. For several reasons, these series are inappropriate to use in studies assessing the rate of output and productivity increases before 1950. We have established new series of output and labour input for manufacturing at large between 1869 and 1950 that are suitable for investigations of productivity growth rates. The resulting series significantly raises the level of output per worker in the early part of the period and hence lowers the estimated growth rates of productivity for the era as a whole.

State of Charge Balancing Control for Multiple Output Dynamically Adjustable Capacity System

&lt;div&gt;A multiple output dynamically adjustable capacity system (MODACS) is developed to provide multiple voltage output levels while supporting varying power loads by switching multiple battery strings between serial and parallel connections. Each module of the system can service either a low voltage bus by placing its strings in parallel or a high voltage bus with its strings in series. Since MODACS contains several such modules, it can produce multiple voltages simultaneously. By switching which strings and modules service the different output rails and by varying the connection strategy over time, the system can balance the states of charge (SOC) of the strings and modules. A model predictive control (MPC) algorithm is formulated to accomplish this balancing. MODACS operates in various power modes, each of which imposes unique constraints on switching between configurations. Those constraints are mathematically formalized so that MPC can be applied to minimize predicted SOC differences over a finite time horizon. In this article, several variations that vary in how freely strings can connect and disconnect from the bus bars are presented. Methods allowing more flexibility in configuration changes can balance SOCs more quickly but take more computation to resolve. In contrast, simpler schemes reduce computation and simplify implementation, but take longer to balance the SOCs. Simulation results illustrate the expected behavior.&lt;/div&gt;

An Experimental Phototherapy Device for Studying the Effects of Blue Light on Patients with Raynaud's Phenomenon.

Raynaud's phenomenon (RP) is a condition that causes decreased blood flow to areas perfused by small blood vessels (e.g., fingers, toes). In severe cases, ulceration, gangrene, and loss of fingers may occur. Most treatments focus on inducing vasorelaxation in affected areas by the way of pharmaceuticals. Recently, animal studies have shown that vasorelaxation can be induced by non-coherent blue light (wavelength ~ 430-460nm) through the actions of melanopsin, a photoreceptive opsin protein encoded by the OPN4 gene. To study this effect in humans, a reliable phototherapy device (PTD) is needed. We outline the construction of a PTD to be used in studying blue light effects on Raynaud's patients. Our design addresses user safety, calibration, electromagnetic compatibility/interference (EMC/EMI), and techniques for measuring physiological responses (temperature sensors, laser Doppler flow sensors, infrared thermal imaging of the hands). We tested our device to ensure (1) safe operating conditions, (2) predictable, user-controlled irradiance output levels, (3) an ability for measuring physiological responses, and (4) features necessary to enable a double-blinded crossover study for a clinical trial. We also include in the Methods an approved research protocol utilizing our device that may serve as a starting point for clinical study. We introduced a reliable PTD for studying the effects of blue light therapy for patients suffering from Raynaud's phenomenon and showed that our device is safe and reliable and includes the required measurement vectors for tracking treatment effects throughout the duration of a clinical study.

A Novel Single-Phase Five-Level Current-Source Inverter Topology

Recent technological advances have renewed the research interest in current-source inverters (CSIs). Nonetheless, CSI research still falls behind its voltage-source counterpart with regards to topologies, modulation, and control. Acknowledging the above, this paper presents a novel single-phase five-level CSI topology. The proposed circuit utilises eight switches and two inductors for the generation of five distinct output levels while maintaining low output voltage THD and dv/dt. Furthermore, by offsetting the inductor currents from a binary 1:2 to a trinary 1:3 ratio, the proposed inverter can generate seven current levels at its output. The inverter offers built-in short-circuit protection and can boost a low input DC voltage to a higher peak AC output voltage. These merits, alongside an electrolytic-capacitor-free design, simple current balancing mechanism, and fault-tolerant characteristics, make it a promising candidate for PV module-integrated inverter (MII) systems. The current topology utilises two inductors but is fully functional with single-inductor operation. The paper provides a functional analysis of the inverter topology alongside the inverter switching states and corresponding conduction paths. A detailed analysis of the inductor current dynamics as well as a current-balancing algorithm for dual- and single-inductor operations are given. The theoretical analysis of the proposed circuit and its functional operation are verified using simulations and experimental results carried out on a laboratory prototype.

Enhancing E-Government Implementation Through Website Management

This study explores the effectiveness of village website management in facilitating e-government implementation within Kebarepan Village, Plumbon District, Cirebon Regency. It assesses four key indicators of program effectiveness: program success, target success, satisfaction with the program, and levels of input and output. Employing a qualitative or naturalistic approach, data were collected through literature review and field study, incorporating observations, interviews, and documentation. Analysis indicates that village website management significantly enhances e-government implementation effectiveness, encompassing program success, target success, satisfaction with the program, and levels of input and output. However, certain obstacles hinder the complete realization of effectiveness. This study enhances comprehension of e-government implementation at the village level and provides insights into addressing existing barriers. The implications of these findings can inform policymakers and practitioners in optimizing e-government effectiveness within village settings.

Nexus between Life Expectancy, CO2 Emissions, Economic Development, Water, and Agriculture in Aral Sea Basin: Empirical Assessment

This study investigates how life expectancy is influenced by CO2 emissions, health spending, GDP, water usage, agricultural output, and renewable and non-renewable energy consumption within the Aral Sea basin, which is an environmentally catastrophic zone in the world. This research utilized data from the years 2002 to 2020 and employed various econometric approaches, including FMOLS, DOLS, and Driscoll–Kraay. The outcomes of the study reveal that health spending, GDP, water productivity, agriculture output, energy consumption, and human capital have a positive impact on life expectancy, but CO2 emissions have a negative impact on life expectancy. The most important policy takeaway from this study is the need to develop and implement comprehensive policies that take into account health spending, GDP, water, agricultural output, energy consumption, and education level in order to ensure life longevity.

Dynamic Cooperative Oligopolies

An n-person cooperative oligopoly is considered without product differentiation. It is assumed that the firms know the unit price function but have no access to the cost functions of the competitors. From market data, they have information about the industry output. The firms want to find the output levels that guarantee maximum industry profit. First, the existence of a unique maximizer is proven, which the firms cannot determine directly because of the lack of the knowledge of the cost functions. Instead, a dynamic model is constructed, which is asymptotically stable under realistic conditions, and the state trajectories converge to the optimum output levels of the firms. Three models are constructed: first, no time delay is assumed; second, information delay is considered for the firms on the industry output; and third, in addition, information delay is also assumed about the firms’ own output levels. The stability of the resulting no-delay, one-delay, and two-delay dynamics is examined.