Effect of different defoliants and application times on the yield and quality components of cotton in semi-arid conditions

This study was conducted to determine the effect of different defoliants (Dropp ultra® (DU): thidiazuron+diuron and Roundup (RU): glyphosate) and application times [60, 75 and 90 days after flowering (DAF)] on cotton. The research was carried out at the Harran University, Faculty of Agriculture Research and Application Center in 2001 and 2002 using cotton variety cv. Stoneville-453. Experiments were arranged as split plot design with three replications. Defoliations were at the main plots and application times at the subplots. Experimental plots were consisted of six rows, 10 m in length, interrow was 0.70 m and intra-row spacing was 0.20 m. The results of the study indicated that the application of DU defoliant at 60 days after flowering reduced seed cotton yield, number of bolls, boll weight and lint index. With this, seed cotton yield, number of bolls, boll weight and lint index increased with delayed defoliation time in both years. Also, there were no statistically significant differences between the treatments in terms of ginning outturn, fiber length, fiber strength and fiber fineness. It was also found that the application of 2000 cc ha-1 RU was not enough as a dose to affect leaf defoliation and other investigated components

Early experience with the ARTISENTIAL® articulated instruments in laparoscopic low anterior resection with TME

Background: The notion of articulation in surgery has been largely synonymous with robotics. The ARTISENTIAL® instruments aim at bringing advanced articulation to laparoscopy to overcome challenges in narrow anatomical spaces. In this paper, we present first single-center results of a series of low anterior resections, performed with ARTISENTIAL®. Methods: Between September 2020 and August 2021, at the Department of Surgery, St. Marienkrankenhaus Siegen, Siegen, Germany, patients with cancer of the mid- and low rectum were prospectively enrolled in a pilot feasibility study to evaluate the ARTISENTIAL® articulated instruments in performing a laparoscopic low anterior resection. Perioperative and short-term postoperative data were analyzed. Results: Seventeen patients (10 males/7 females) were enrolled in this study. The patients had a median age of 66 years (range 47–80 years) and a median body mass index of 28 kg/m2 (range 23–33 kg/m2). The median time to rectal transection was 155 min (range 118–280 min) and the median total operative time was 276 min (range 192–458 min). The median estimated blood loss was 30 ml (range 5–70 ml) and there were no conversions to laparotomy. The median number of harvested lymph nodes was 15 (range 12–28). Total mesorectal excision (TME) quality was ‘good’ in all patients with no cases of circumferential resection margin involvement (R0 = 100%). The median length of stay was 9 days (range 7–14 days). There were no anastomotic leaks and the overall complication rate was 17.6%. There was one unrelated readmission with no mortality. Conclusions: Low anterior resection with ARTISENTIAL® is feasible and safe. All patients had a successful TME procedure with a good oncological outcome. We will now seek to evaluate the benefits of ARTISENTIAL® in comparison with standard laparoscopic instruments through a larger study

An integrated approach of multiple correspondences analysis (MCA) and fuzzy AHP method for occupational health and safety performance evaluation in the land cargo transportation

Land cargo transportation is one of the components of the logistics chain with high impact on economic and social development worldwide. However, problems such as top logistics costs, deficiencies in transportation infrastructure and the failure to adopt good operating practices in aspects such as quality, environment, and occupational safety and health affect the ability of companies to comply with the agreements, requirements, and regulations of the clients and other interested parties. One of the most relevant problems for the sector is associated with the high accident rates that make this medium less advantageous compared to other means of transport with impact on operational costs, on logistics indicators, on compliance with legal regulations and customer satisfaction. However, although there are legal standards and management standards in occupational safety and health, evaluating performance can become a difficult and subjective process, due to the complexity of the land cargo transportation and the different interest groups involved. Besides, there is little information in the literature that provides solutions for the industry. Therefore, this document presents an integrated approach between multi-criterion decision making models (MCDM) and the Multiple Correspondences Analysis (MCA) to facilitate the evaluation and improvement of occupational health and safety performance, with a logical process, objective, robust and using both qualitative and quantitative techniques, with real application in the land cargo transportation sector. First, the multivariate method of Multiple Correspondences Analysis (MCA) was used for the evaluation of a sample of companies in the industry, considering the factors and sub-factors identified in the first stage and performing correlational analyzes among the variables. Subsequently, a multicriteria decision-making model was designed to determine the factors and sub-factors that affect occupational health and safety performance through the technique of the Fuzzy Analytic Hierarchy Process (FAHP). Finally, improvement strategies are proposed based on the approaches suggested in this document

Predicting Important Residues and Interaction Pathways in Proteins Using Gaussian Network Model: Binding and Stability of HLA Proteins

A statistical thermodynamics approach is proposed to determine structurally and functionally important residues in native proteins that are involved in energy exchange with a ligand and other residues along an interaction pathway. The structure-function relationships, ligand binding and allosteric activities of ten structures of HLA Class I proteins of the immune system are studied by the Gaussian Network Model. Five of these models are associated with inflammatory rheumatic disease and the remaining five are properly functioning. In the Gaussian Network Model, the protein structures are modeled as an elastic network where the inter-residue interactions are harmonic. Important residues and the interaction pathways in the proteins are identified by focusing on the largest eigenvalue of the residue interaction matrix. Predicted important residues match those known from previous experimental and clinical work. Graph perturbation is used to determine the response of the important residues along the interaction pathway. Differences in response patterns of the two sets of proteins are identified and their relations to disease are discussed

Specificity of Trypsin and Chymotrypsin: Loop Motion Controlled Dynamic Correlation as a Determinant

Trypsin and chymotrypsin are both serine proteases with high sequence and structural similarities, but with different substrate specificity. Previous experiments have demonstrated the critical role of the two loops outside the binding pocket in controlling the specificity of the two enzymes. To understand the mechanism of such a control of specificity by distant loops, we have used the Gaussian Network Model to study the dynamic properties of trypsin and chymotrypsin and the roles played by the two loops. A clustering method was introduced to analyze the correlated motions of residues. We have found that trypsin and chymotrypsin have distinct dynamic signatures in the two loop regions which are in turn highly correlated with motions of certain residues in the binding pockets. Interestingly, replacing the two loops of trypsin with those of chymotrypsin changes the motion style of trypsin to chymotrypsin-like, whereas the same experimental replacement was shown necessary to make trypsin have chymotrypsin's enzyme specificity and activity. These results suggest that the cooperative motions of the two loops and the substrate-binding sites contribute to the activity and substrate specificity of trypsin and chymotrypsin.Comment: 41 pages, 7 figure

Screened non-bonded interactions in native proteins manipulate optimal paths for robust residue communication

A protein structure is represented as a network of residues whereby edges are determined by intra-molecular contacts. We introduce inhomogeneity into these networks by assigning each edge a weight that is determined by amino-acid pair potentials. Two methodologies are utilized to calculate the average path lengths (APLs) between pairs: To minimize (i) the maximum weight in the strong APL, and (ii) the total weight in the weak APL. We systematically screen edges that have higher than a cutoff potential and calculate the shortest APLs in these reduced networks, while keeping chain connectivity. Therefore, perturbations introduced at a selected region of the residue network propagate to remote regions only along the non-screened edges that retain their ability to disseminate the perturbation. The shortest APLs computed from the reduced homogeneous networks with only the strongest few non-bonded pairs closely reproduce the strong APLs from the weighted networks. The rate of change in the APL in the reduced residue network as compared to its randomly connected counterpart remains constant until a lower bound. Upon further link removal, this property shows an abrupt increase, towards a random coil behavior. Under different perturbation scenarios, diverse optimal paths emerge for robust residue communication.Comment: 21 pages with 6 figure

How to create an operational multi-model of seasonal forecasts?

Seasonal forecasts of variables like near-surface temperature or precipitation are becoming increasingly important for a wide range of stakeholders. Due to the many possibilities of recalibrating, combining, and verifying ensemble forecasts, there are ambiguities of which methods are most suitable. To address this we compare approaches how to process and verify multi-model seasonal forecasts based on a scientific assessment performed within the framework of the EU Copernicus Climate Change Service (C3S) Quality Assurance for Multi-model Seasonal Forecast Products (QA4Seas) contract C3S 51 lot 3. Our results underpin the importance of processing raw ensemble forecasts differently depending on the final forecast product needed. While ensemble forecasts benefit a lot from bias correction using climate conserving recalibration, this is not the case for the intrinsically bias adjusted multi-category probability forecasts. The same applies for multi-model combination. In this paper, we apply simple, but effective, approaches for multi-model combination of both forecast formats. Further, based on existing literature we recommend to use proper scoring rules like a sample version of the continuous ranked probability score and the ranked probability score for the verification of ensemble forecasts and multi-category probability forecasts, respectively. For a detailed global visualization of calibration as well as bias and dispersion errors, using the Chi-square decomposition of rank histograms proved to be appropriate for the analysis performed within QA4Seas.The research leading to these results is part of the Copernicus Climate Change Service (C3S) (Framework Agreement number C3S_51_Lot3_BSC), a program being implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) on behalf of the European Commission. Francisco Doblas-Reyes acknowledges the support by the H2020 EUCP project (GA 776613) and the MINECO-funded CLINSA project (CGL2017-85791-R)

Innovation and growth in the UK pharmaceuticals: the case of product and marketing introductions

New drug introductions are key to growth for pharmaceutical firms. However, not all innovations are the same and they may have differential effects that vary by firm size. We use quarterly sales data on UK pharmaceuticals in a dynamic panel model to estimate the impact of product (new drugs) and marketing (additional pack varieties) innovations within a therapeutic class on a firm’s business unit growth. We find that product innovations lead to substantial growth in both the short and long run, whereas a new pack variety only produces short-term effects. The strategies are substitutes but the marginal effects are larger for product innovations relative to additional packs, and the effects are larger for smaller business units. Nonetheless, pack introductions offer a viable short-term growth strategy, especially for small- and medium-sized businesses

Sustainable Waste-to-Energy Technologies: Bioelectrochemical Systems

The food industry produces a large amount of waste and wastewater, of which most of the constituents are carbohydrates, proteins, lipids, and organic fibers. Therefore food wastes are highly biodegradable and energy rich. Bioelectrochemical systems (BESs) are systems that use microorganisms to biochemically catalyze complex substrates into useful energy products, in which the catalytic reactions take place on electrodes. Microbial fuel cells (MFCs) are a type of bioelectrochemical systems that oxidize substrates and generate electric current. Microbial electrolysis cells (MECs) are another type of bioelectrochemical systems that use an external power source to catalyze the substrate into by-products such as hydrogen gas, methane gas, or hydrogen peroxide. BESs are advantageous due to their ability to achieve a degree of substrate remediation while generating energy. This chapter presents an extensive literature review on the use of MFCs and MECs to remediate and recover energy from food industry waste. These bioelectrochemical systems are still in their infancy state and further research is needed to better understand the systems and optimize their performance. Major challenges and limitations for the use of BESs are summarized and future research needs are identified