Demand forecasting process design and methods in medium sized enterprise

The purpose of this thesis was to study the design of demand forecasting processes and management of demand. In literature review were different processes found and forecasting methods and techniques interviewed. Also role of bullwhip effect in supply chain was identified and how to manage it with information sharing operations. In the empirical part of study is at first described current situation and challenges in case company. After that will new way to handle demand introduced with target budget creation and how information sharing with 5 products and a few customers would bring benefits to company. Also the new S&OP process created within this study and organization for it.

Aluminum induces lipid peroxidation and aggregation of human blood platelets

Aluminum (Al3+) intoxication is thought to play a major role in the development of Alzheimer's disease and in certain pathologic manifestations arising from long-term hemodialysis. Although the metal does not present redox capacity, it can stimulate tissue lipid peroxidation in animal models. Furthermore, in vitro studies have revealed that the fluoroaluminate complex induces diacylglycerol formation, 43-kDa protein phosphorylation and aggregation. Based on these observations, we postulated that Al3+-induced blood platelet aggregation was mediated by lipid peroxidation. Using chemiluminescence (CL) of luminol as an index of total lipid peroxidation capacity, we established a correlation between lipid peroxidation capacity and platelet aggregation. Al3+ (20-100 µM) stimulated CL production by human blood platelets as well as their aggregation. Incubation of the platelets with the antioxidants nor-dihydroguaiaretic acid (NDGA) (100 µM) and n-propyl gallate (NPG) (100 µM), inhibitors of the lipoxygenase pathway, completely prevented CL and platelet aggregation. Acetyl salicylic acid (ASA) (100 µM), an inhibitor of the cyclooxygenase pathway, was a weaker inhibitor of both events. These findings suggest that Al3+ stimulates lipid peroxidation and the lipoxygenase pathway in human blood platelets thereby causing their aggregation

Low levels of sex hormone-binding globulin and hyperproinsulinemia as markers of increased pancreatic ß-cell demand in men

Low levels of sex hormone-binding globulin (SHBG) are considered to be an indirect index of hyperinsulinemia, predicting the later onset of diabetes mellitus type 2. In the insulin resistance state and in the presence of an increased pancreatic ß-cell demand (e.g. obesity) both absolute and relative increases in proinsulin secretion occur. In the present study we investigated the correlation between SHBG and pancreatic ß-cell secretion in men with different body compositions. Eighteen young men (30.0 ± 2.4 years) with normal glucose tolerance and body mass indexes (BMI) ranging from 22.6 to 43.2 kg/m2 were submitted to an oral glucose tolerance test (75 g) and baseline and 120-min blood samples were used to determine insulin, proinsulin and C-peptide by specific immunoassays. Baseline SHBG values were significantly correlated with baseline insulin (r = -0.58, P<0.05), proinsulin (r = -0.47, P<0.05), C-peptide (r = -0.55, P<0.05) and also with proinsulin at 120 min after glucose load (r = -0.58, P<0.05). Stepwise regression analysis revealed that proinsulin values at 120 min were the strongest predictor of SHBG (r = -0.58, P<0.05). When subjects were divided into obese (BMI >28 kg/m2, N = 8) and nonobese (BMI £25 kg/m2, N = 10) groups, significantly lower levels of SHBG were found in the obese subjects. The obese group had significantly higher baseline proinsulin, C-peptide and 120-min proinsulin and insulin levels. For the first time using a specific assay for insulin determination, a strong inverse correlation between insulinemia and SHBG levels was confirmed. The finding of a strong negative correlation between SHBG levels and pancreatic ß-cell secretion, mainly for the 120-min post-glucose load proinsulin levels, reinforces the concept that low SHBG levels are a suitable marker of increased pancreatic ß-cell demand.

Determination of serum aluminum, platelet aggregation and lipid peroxidation in hemodialyzed patients

Aluminum (Al3+) overload is frequently associated with lipid peroxidation and neurological disorders. Aluminum accumulation is also reported to be related to renal impairment, anemia and other clinical complications in hemodialysis patients. The aim of the present study was to determine the degree of lipid peroxidation, platelet aggregation and serum aluminum in patients receiving regular hemodialytic treatment. The level of plasma lipid peroxidation was evaluated on the basis of thiobarbituric acid reactive substances (TBARS). Mean platelet peroxidation in patients undergoing hemodialysis was significantly higher than in normal controls (2.7 ± 0.03 vs 1.8 ± 0.06 nmol/l, P<0.05). Platelet aggregation and serum aluminum levels were determined by a turbidimetric method and atomic absorption spectrophotometry, respectively. Serum aluminum was significantly higher in patients than in normal controls (44.5 ± 29 vs 10.8 ± 2.5 µg/l, P<0.05). Human blood platelets were stimulated with collagen (2.2 µg/ml), adenosine diphosphate (6 µM) and epinephrine (6 µM) and showed reduced function with the three agonists utilized. No correlation between aluminum levels and platelet aggregation or between aluminum and peroxidation was observed in hemodialyzed patients.

Genomics and X-ray microanalysis indicate that Ca2+ and thiols mediate the aggregation and adhesion of Xylella fastidiosa

The availability of the genome sequence of the bacterial plant pathogen Xylella fastidiosa, the causal agent of citrus variegated chlorosis, is accelerating important investigations concerning its pathogenicity. Plant vessel occlusion is critical for symptom development. The objective of the present study was to search for information that would help to explain the adhesion of X. fastidiosa cells to the xylem. Scanning electron microscopy revealed that adhesion may occur without the fastidium gum, an exopolysaccharide produced by X. fastidiosa, and X-ray microanalysis demonstrated the presence of elemental sulfur both in cells grown in vitro and in cells found inside plant vessels, indicating that the sulfur signal is generated by the pathogen surface. Calcium and magnesium peaks were detected in association with sulfur in occluded vessels. We propose an explanation for the adhesion and aggregation process. Thiol groups, maintained by the enzyme peptide methionine sulfoxide reductase, could be active on the surface of the bacteria and appear to promote cell-cell aggregation by forming disulfide bonds with thiol groups on the surface of adjacent cells. The enzyme methionine sulfoxide reductase has been shown to be an auxiliary component in the adhesiveness of some human pathogens. The negative charge conferred by the ionized thiol group could of itself constitute a mechanism of adhesion by allowing the formation of divalent cation bridges between the negatively charged bacteria and predominantly negatively charged xylem walls.

The demand-supply balancing process in supply chain management - case mining & metals industry equipment

The aim of this thesis is to search how to match the demand and supply effectively in industrial and project-oriented business environment. The demand-supply balancing process is searched through three different phases: the demand planning and forecasting, synchronization of demand and supply and measurement of the results. The thesis contains a single case study that has been implemented in a company called Outotec. In the case study the demand is planned and forecasted with qualitative (judgmental) forecasting method. The quantitative forecasting methods are searched further to support the demand forecast and long term planning. The sales and operations planning process is used in the synchronization of the demand and supply. The demand forecast is applied in the management of a supply chain of critical unit of elemental analyzer. Different meters on operational and strategic level are proposed for the measurement of performance.

Utilization of AMI-Technology in a Multilayered Demand Response Service Environment

This thesis studied the performance of Advanced metering infrastructure systems in a challenging Demand Response environment. The aim was to find out what kind of challenges and bottlenecks could be met when utilizing AMI-systems in challenging Demand Response tasks. To find out the challenges and bottlenecks, a multilayered demand response service concept was formed. The service consists of seven different market layers which consist of Nordic electricity market and the reserve markets of Fingrid. In the simulations the AMI-systems were benchmarked against these seven market layers. It was found out, that the current generation AMI-systems were capable of delivering Demand Response on the most challenging market layers, when observed from time critical viewpoint. Additionally, it was found out, that to enable wide scale Demand Response there are three major challenges to be acknowledged. The challenges hindering the utilization of wide scale Demand Response were related to poor standardization of the systems in use, possible problems in data connectivity solutions and the current electricity market regulation model.

Accuracy improvement of a demand forecasting model

This research concerns different statistical methods that assist to increase the demand forecasting accuracy of company X’s forecasting model. Current forecasting process was analyzed in details. As a result, graphical scheme of logical algorithm was developed. Based on the analysis of the algorithm and forecasting errors, all the potential directions for model future improvements in context of its accuracy were gathered into the complete list. Three improvement directions were chosen for further practical research, on their basis, three test models were created and verified. Novelty of this work lies in the methodological approach of the original analysis of the model, which identified its critical points, as well as the uniqueness of the developed test models. Results of the study formed the basis of the grant of the Government of St. Petersburg.

Evaluating and improving demand forecast practices for B2B and B2C sectors

Demand forecasting is one of the fundamental managerial tasks. Most companies do not know their future demands, so they have to make plans based on demand forecasts. The literature offers many methods and approaches for producing forecasts. Former literature points out that even though many forecasting methods and approaches are available, selecting a suitable approach and implementing and managing it is a complex cross-functional matter. However, it’s relatively rare that researches are focused on the differences in forecasting between consumer and industrial companies. The aim of this thesis is to investigate the potential of improving demand forecasting practices for B2B and B2C sectors in the global supply chains. Business to business (B2B) sector produces products for other manufacturing companies. On the other hand, consumer (B2C) sector provides goods for individual buyers. Usually industrial sector have a lower number of customers and closer relationships with them. The research questions of this thesis are: 1) What are the main differences and similarities in demand planning between B2B and B2C sectors? 2) How the forecast performance for industrial and consumer companies can be improved? The main methodological approach in this study is design science, where the main objective is to develop tentative solutions to real-life problems. The research data has been collected from a case company. Evaluation and improving in organizing demand forecasting can be found in three interlinked areas: 1) demand planning operational environment, 2) demand forecasting techniques, 3) demand information sharing scenarios. In this research current B2B and B2C demand practices are presented with further comparison between those two sectors. It was found that B2B and B2C sectors have significant differences in demand practices. This research partly filled the theoretical gap in understanding the difference in forecasting in consumer and industrial sectors. In all these areas, examples of managerial problems are described, and approaches for mitigating these problems are outlined.

Quantitative evidence for neurofilament heavy subunit aggregation in motor neurons of spinal cords of patients with amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS), a neurodegenerative disease of unknown etiology, affects motor neurons leading to atrophy of skeletal muscles, paralysis and death. There is evidence for the accumulation of neurofilaments (NF) in motor neurons of the spinal cord in ALS cases. NF are major structural elements of the neuronal cytoskeleton. They play an important role in cell architecture and differentiation and in the determination and maintenance of fiber caliber. They are composed of three different polypeptides: light (NF-L), medium (NF-M) and heavy (NF-H) subunits. In the present study, we performed a morphological and quantitative immunohistochemical analysis to evaluate the accumulation of NF and the presence of each subunit in control and ALS cases. Spinal cords from patients without neurological disease and from ALS patients were obtained at autopsy. In all ALS cases there was a marked loss of motor neurons, besides atrophic neurons and preserved neurons with cytoplasmic inclusions, and extensive gliosis. In control cases, the immunoreaction in the cytoplasm of neurons was weak for phosphorylated NF-H, strong for NF-M and weak for NF-L. In ALS cases, anterior horn neurons showed intense immunoreactivity in focal regions of neuronal perikarya for all subunits, although the difference in the integrated optical density was statistically significant only for NF-H. Furthermore, we also observed dilated axons (spheroids), which were immunopositive for NF-H but negative for NF-M and NF-L. In conclusion, we present qualitative and quantitative evidence of NF-H subunit accumulation in neuronal perikarya and spheroids, which suggests a possible role of this subunit in the pathogenesis of ALS.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

CCN2/CTGF silencing blocks cell aggregation in embryonal carcinoma P19 cell

Connective tissue growth factor (CCN2/CTGF) is a matricellular-secreted protein involved in extracellular matrix remodeling. The P19 cell line is an embryonic carcinoma line widely used as a cellular model for differentiation and migration studies. In the present study, we employed an exogenous source of CCN2 and small interference RNA to address the role of CCN2 in the P19 cell aggregation phenomenon. Our data showed that increasing CCN2 protein concentrations from 0.1 to 20 nM decreased the number of cell clusters and dramatically increased cluster size without changing proliferation or cell survival, suggesting that CCN2 induced aggregation. In addition, CCN2 specific silencing inhibited typical P19 cell aggregation, which could be partially rescued by 20 nM CCN2. The present study demonstrates that CCN2 is a key molecule for cell aggregation of embryonic P19 cells.

Addressing conflicts of interest in the research paper: a societal demand in contemporary science?

In the last decade, dialogue between science and society has found a forum in an increasing number of publications on topics such as public engagement with science and public trust in science. Concerning the latter, issues that include cases of research misconduct, accountability in research, and conflicts of interest (COIs) have shaped global discussions on the communication of science. In the publication setting, the perception that hiding COIs and/or not managing them well may affect public trust in the research record has grown among editors. We conducted a search for editorials addressing COIs between 1989 and 2011, using four major databases: Medline/PubMed, Embase, Scopus, and Web of Knowledge. We explored the content of these editorials and the relationship they established between COIs and the public trust in science. Our results demonstrate that the relationship between disclosure of COIs and public trust in science has become a major concern among editors. We, thus, argue that COIs should be discussed more openly and frequently in graduate courses in the sciences, around the globe, not only in biomedical but also in non-biomedical areas. This is a critical issue in contemporary science, as graduate students are the future voices and decision-makers of the research community. Therefore, COIs, especially in the broader context of science and society, merit closer attention from policymakers, researchers, and educators. At times of great expectations for public engagement with science, mishandling of COIs may have undesirable consequences for public engagement with science and confidence in the scientific endeavor.

Effects of simvastatin/ezetimibe on microparticles, endothelial progenitor cells and platelet aggregation in subjects with coronary heart disease under antiplatelet therapy

It is not known whether the addition of ezetimibe to statins adds cardiovascular protection beyond the expected changes in lipid levels. Subjects with coronary heart disease were treated with four consecutive 1-week courses of therapy (T) and evaluations. The courses were: T1, 100 mg aspirin alone; T2, 100 mg aspirin and 40 mg simvastatin/10 mg ezetimibe; T3, 40 mg simvastatin/10 mg ezetimibe, and 75 mg clopidogrel (300 mg initial loading dose); T4, 75 mg clopidogrel alone. Platelet aggregation was examined in whole blood. Endothelial microparticles (CD51), platelet microparticles (CD42/CD31), and endothelial progenitor cells (CD34/CD133; CDKDR/CD133, or CD34/KDR) were quantified by flow cytometry. Endothelial function was examined by flow-mediated dilation. Comparisons between therapies revealed differences in lipids (T2 and T3T1 and T4, P=0.001). Decreased platelet aggregation was observed after aspirin (arachidonic acid, T1aggregation, the amount of circulating endothelial and platelet microparticles, or endothelial progenitor cells. Cardiovascular protection following therapy with simvastatin/ezetimibe seems restricted to lipid changes and improvement of endothelial function not affecting the release of microparticles, mobilization of endothelial progenitor cells or decreased platelet aggregation.

Households’ willingness to engage in demand response in the Finnish retail electricity market: an empirical study

If electricity users adjusted their consumption patterns according to time-variable electricity prices or other signals about the state of the power system, generation and network assets could be used more efficiently, and matching intermittent renewable power generation with electricity demand would be facilitated. This kind of adjustment of electricity consumption, or demand response, may be based on consumers’ decisions to shift or reduce electricity use in response to time-variable electricity prices or on the remote control of consumers’ electric appliances. However, while demand response is suggested as a solution to many issues in power systems, actual experiences from demand response programs with residential customers are mainly limited to short pilots with a small number of voluntary participants, and information about what kinds of changes consumers are willing and able to make and what motivates these changes is scarce. This doctoral dissertation contributes to the knowledge about what kinds of factors impact on residential consumers’ willingness and ability to take part in demand response. Saving opportunities calculated with actual price data from the Finnish retail electricity market are compared with the occurred supplier switching to generate a first estimate about how large savings could trigger action also in the case of demand response. Residential consumers’ motives to participate in demand response are also studied by a web-based survey with 2103 responses. Further, experiences of households with electricity consumption monitoring systems are discussed to increase knowledge about consumers’ interest in getting more information on their electricity use and adjusting their behavior based on it. Impacts of information on willingness to participate in demand response programs are also approached by a survey for experts of their willingness to engage in demand response activities. Residential customers seem ready to allow remote control of electric appliances that does not require changes in their everyday routines. Based on residents’ own activity, the electricity consuming activities that are considered shiftable are very limited. In both cases, the savings in electricity costs required to allow remote control or to engage in demand response activities are relatively high. Nonmonetary incentives appeal to fewer households.