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The Asian Handicap is a way to bet on soccer matches where payouts depend on an adjustment to the score that favors the weaker team. These bets can feature the possibility of all or half the bet being refunded and this makes the calculation of their expected return more complex than for traditional betting on a home win, away win or draw. We examine the behavior of odds in this market.

In addition to a using well-known publicly available source of information on Asian Handicap betting odds – which provides the average odds across a range of bookmakers – we have also sourced a large dataset of Asian Handicap odds offered by an individual bookmaker.

We show that bettors systematically lose more money on Asian Handicap bets where refunds are not possible than when it is possible to obtain a half refund. We also show that bets with the possibility of a full refund have the lowest loss rates. We demonstrate that this pattern of differences in loss rates across bets is predictable based on the odds quoted. This pattern could represent preferences, with gamblers disliking bets featuring potential refunds, but we argue the evidence points more towards gamblers incorrectly calculating expected loss rates.

Despite being one of the world's largest betting markets, there has been almost no previous research on the properties of the Asian Handicap soccer betting. Our finding of clear differences in returns on simultaneously available bets on the same team is also a new anomaly previously undocumented in any research on sports betting.

The purpose of this study is to evaluate and minimize the losses of alternating current (AC) in the winding of electrical machines. AC winding losses are frequently disregarded at low frequencies, but they become a significant concern at high frequencies. This is the situation where applications require a high speed. The most significant applications in this category are electrical propulsion and drive systems.

An analytical model is used to predict the AC losses in the winding of electrical machines. The process involves dividing the slot into separate layers and then calculating the AC loss factor for each layer. The model aims to calculate AC losses for two different winding arrangements involving circular conductors. This application focuses on the stator winding of a permanent magnet synchronous motor that is specifically designed for electric vehicles. The model is integrated into an optimization process that makes use of the genetic algorithm method to minimize AC losses resulting from the arrangement of conductors within the slot.

This study and its findings demonstrate that the arrangement of the conductors within the slot has a comparable effect on the AC losses in the winding as the machine's geometric and physical properties. The effectiveness of electrical machines depends heavily on optimizing the arrangement of conductors in the slot to minimize AC winding losses.

The proposed strategy seeks to minimize AC winding losses in high-speed electric machines by providing a cost-effective and precise solution to improve energy efficiency.

This paper aims to propose a method for automatic design of additive manufacturing (AM) flow channel paths driven by path length and pressure loss. The research focuses on the automatic design of channel paths, intending to achieve the shortest flow channel length or minimum pressure loss and improve the design efficiency of AM parts.

The initial layout of the flow channels is redesigned to consider the channels print supports. Boundary conditions and constraints are defined according to the redesigned channels layout, and the equation consisting of channel length and pressure loss is used as the objective function. Then the path planning simulation is performed based on particle swarm algorithm. The proposed method describes the path of flow channels using spline cures. The spline curve is controlled by particle (one particle represents a path), and the particle is randomly generated within the design space. After the path planning simulation is completed, the generated paths are used to create 3D parts.

Case study 1 demonstrates the automatic design of hydraulic spool valve. Compared to conventional spool valve, the pressure loss was reduced by 86% and the mass was reduced by 83%. The design results of case study 2 indicate that this approach is able to find the shortest channel path with lower computational cost.

The automatic design method of flow channel paths driven by path length and pressure loss presented in this paper provides a novel solution for the creation of AM flow components.

This study aims to develop a simplified bioink preparation method that can be applied to most hydrogel bioinks used in extrusion-based techniques.

The parameters of the bioprinting process significantly affect the printability of the bioink and the viability of cells. In turn, the bioink formulation and its physicochemical properties may influence the appropriate range of printing parameters. In extrusion-based bioprinting, the rheology of the bioink affects the printing pressure, cell survival and structural integrity. Three concentrations of alginate-gelatin hydrogel were prepared and printed at three different flow rates and nozzle gauges to investigate the print parameters. Other characterizations were performed to evaluate the hydrogel structure, printability, gelation time, swelling and degradation rates of the bioink and cell viability. An experimental design was used to determine optimal parameters. The analyses included live/dead assays, rheological measurements, swelling and degradation.

The experimental design results showed that the hydrogel flow rate substantially influenced printing accuracy and pressure. The best hydrogel flow rate in this study was 10 ml/h with a nozzle gauge of 18% and 4% alginate. Three different concentrations of alginate-gelatin hydrogels were found to exhibit shear-thinning behavior during printing. After seven days, 46% of the structure in the 4% alginate-5% gelatin sample remained intact. After printing, the viability of skin fibroblast cells for the optimized sample was 91%.

This methodology offers a straightforward bioink preparation method applicable to the majority of hydrogels used in extrusion-based procedures. This can also be considered a prerequisite for cell printing.

This study aims to evaluate the nutrient content and acceptable qualities of plant-based burger patties (PBBP) formulated with chickpea flour, defatted sesame cake (DSC) flour, coffee silver skin and pomegranate juice as colorant.

The chemical composition, energy value, cholesterol content, amino acid composition, cooking loss, pH, color characteristics and sensory attributes of PBBP were analyzed using official procedures and compared to beef burger. 

PBBP had a protein value of 16.0 g/100g, which is nearly close to the protein content of the beef burger (18.1 g/100g). The fat content of the PBBP was approximately three times lower than that of the beef burger. The fiber content in PBBP was approximately 23 times as high as that in beef burgers samples (p = 0.05). The raw PBBP samples supplies 178 Kcal/100g, whereas beef burger possessed 259 Kcal/100g. Neither the raw nor the cooked PBBP samples contained any cholesterol. Both the beef and PBBP displayed acceptability scores higher than 7.0, which suggests that PBBP was well accepted.

It is concluded that the PBBP sample exhibited a protein value of 16.0 g/100g, which is comparable to the protein level of beef burgers (18.1 g/100g). The fat level of the PBBP samples was significantly lower than that of the beef burger samples. Uncooked PBBP samples contained significantly higher fiber content compared to beef burger samples. No cholesterol was found in raw or cooked PBBP samples. Overall acceptance scores for both beef and PBBP samples exceeded 7.0, suggesting that the proposed product (PBBP) was received favorably.

This study aims to investigate the satisfaction of farmers with the compensation policy for wildlife-caused damages and its influencing factors, analyze the current situation of satisfaction with the compensation policy among farmers, identify factors significantly affecting satisfaction, and explore ways to optimize the compensation policy and improve the satisfaction of farmers based on the effects of various influencing factors.

The Xishuangbanna National Nature Reserve in Yunnan Province, China, is selected as the research area for the study. Through field interviews, 370 valid questionnaires were collected to obtain relevant data on farmers' satisfaction with the compensation policy for wildlife-caused damages. The Oprobit model is utilized to explore the factors influencing farmer satisfaction and to analyze their underlying reasons.

The study reveals that farmers in the communities surrounding the Xishuangbanna National Nature Reserve generally experience low satisfaction with the compensation policy, particularly concerning satisfaction with compensation amounts, which tends to be dissatisfied on average. Satisfaction with the compensation policy is significantly influenced by individual characteristics and household labor structure, while the degree of human-wildlife conflict, wildlife conservation attitudes and household income structure have insignificant impact. Among individual characteristics, gender, education level, health status, and ethnicity are highly significant. In household labor structure, the number of agricultural laborers, non-agricultural laborers, and household agricultural labor time are highly significant.

Building on the overall satisfaction of farmers with the compensation policy, this study further decomposes policy satisfaction into satisfaction with compensation amounts, coverage, and procedures. It provides more targeted recommendations for enhancing satisfaction with the compensation policy, which can help effectively mitigate human-wildlife conflicts and achieve harmonious coexistence between humans and nature.

Managing weeds and pests in cropland is one of the major concerns in agriculture that greatly affects the quantity and quality of the produce. While the success of preventing potential weeds and pests is not guaranteed, early detection and diagnosis help manage them effectively to ensure crops’ growth and health

We propose a diagnostic framework for crop management with automatic weed and pest detection and identification in maize crops using residual neural networks. We train two models, one for weed detection with a labeled image dataset of maize and commonly occurring weed plants, and another for leaf disease detection using a labeled image dataset of healthy and infected maize leaves. The global and local explanations of image classification are obtained and presented

Weed and disease detection and identification can be accurately performed using deep-learning neural networks. Weed detection is accurate up to 97%, and disease detection up to 95% is made on average and the results are presented. Further, using this crop management system, we can detect the presence of weeds and pests in the maize crop early, and the annual yield of the maize crop can potentially increase by 90% theoretically with suitable control actions

The proposed diagnostic models can be further used on farms to monitor the health of maize crops. Images obtained from drones and robots can be fed to these models, which can then automatically detect and identify weed and disease attacks on maize farms. This offers early diagnosis, which enables necessary treatment and control of crops at the early stages without affecting the yield of the maize crop

The proposed crop management framework allows treatment and control of weeds and pests only in the affected regions of the farms and hence minimizes the use of harmful pesticides and herbicides and their related health effects on consumers and farmers.

This study presents an integrated weed and disease diagnostic framework, which is scarcely reported in the literature

The purpose of this paper is to investigate the effect of laser peening (LP) on mechanical and wear properties of 304 stainless steel sheet.

Three-dimensional morphology, micro-hardness and micro-structure of shocked samples were tested. The wear amount, wear track morphology and wear mechanism were also characterized under dry sliding wear using Al₂O₃ ceramics ball.

The LP treatment generates deformation twins that contribute to the grain refinement and hardness increase. The wear test displays that the wear mechanism of samples is mainly abrasive wear and oxidation wear at 10 N load. While at 30 N, the delamination and adhesion areas of treated sample are reduced visibly compared to untreated ones.

This study specifically investigates the mechanical and wear properties of 304 stainless steel after the direct action of LP on its surface, which shows an effective improvement on the wear resistance. For example, the wear loss of processed sample is reduced by 19% at 30 N, the friction coefficient decreases from 0.4714 to 0.4308 and the groove depth is reduced from 78.1 to 74.4 µm under same condition.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2024-0007/

Low-carbon concrete represents a new direction in mitigating the global warming effects caused by clinker manufacturing. Utilizing Saudi agro-industrial by-products as an alternative to cement is a key support in reducing clinker production and promoting innovation in infrastructure and circular economy concepts, toward decarbonization in the construction industry. The use of fly ash (FA) as a cement alternative has been researched and proven effective in enhancing the durability of FA-based concrete, especially at lower replacement levels. However, at higher replacement levels, a noticeable impediment in mechanical strength indicators limits the use of this material.

In this study, low-carbon concrete mixes were designed by replacing 50% of the cement with FA. Varying ratios of nano-sized glass powder (4 and 6% of cement weight) were used as nanomaterial additives to enhance the mechanical properties and durability of the designed concrete. In addition, a 10% of the mixing water was replaced with EMs dosage.

The results obtained showed a significant positive impact on resistance and durability properties when replacing 10% of the mixing water with effective microorganisms (EMs) broth and incorporating nanomaterial additives. The optimal mix ratios were those designed with 10% EMs and 4–6% nano-sized glass powder additives. However, it can be concluded that advancements in eco-friendly concrete additive technologies have made significant contributions to the development of sophisticated concrete varieties.

This study focused at developing nanomaterial additives from Saudi industrial wastes and at presenting a cost-effective and feasible solution for enhancing the properties of FA-based concrete. It has also been found that the inclusion of EMs contributes effectively to enhancing the concrete's resistance properties.

Considering the financial service providers’ (FSPs) information asymmetry in evaluating the supplier and their distinct quit probabilities, we want to examine the supplier’s preference of the financing schemes if both the bank and the online platform exist and how the buyer sets the contract terms in the two financing schemes.

We establish a Stackelberg game model to capture the interactions among three parties, i.e. a supplier, a capital-sufficient buyer and an FSP (either a bank or an online platform), within a first-time contract.

In the non-FSPs’ quit case, the buyer’s profit is higher under the bank loan scenario, while the supplier’s profit performs adversely. The supply chain’s profit is heavily dependent on the buyer’s profit difference between the two financing schemes. Moreover, we find that the supplier borrows the money to exactly cover the production cost. The equilibrium solutions of the FSPs’ quit case and of the capital-sufficient supplier’s case are also derived.

First, we assign different risk profiles to different FSPs in our setting so that modeling a previously ignored but practically significant problem. Second, we innovatively take the FSP’s quit probability into account in our model. Third, we elucidate how these factors can influence the relative efficiency of the two types of financing schemes and the settings of the contract, which further complements and extends the current SCF research.