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A fundamental component of human intelligence is the capacity for feeling. In addition to being founded on logic and reason, human conduct is also greatly influenced by the emotions that people experience. For the purpose of this study, we classified one thousand real-life call center client voice data in the Turkish language based on the way they expressed their emotions using text emotion detection. We made use of Ekman's emotional labeling and techniques from the field of artificial intelligence, such as deep learning and other similar methods.

Rituximab was first used as a treatment for B-cell malign lymphoma, and it is currently used in the treatment of rheumatoid arthritis. On the other hand, an association between rheumatoid arthritis with another autoimmune disease Hashimoto’s thyroiditis is a condition that can be expected. Thirty-four-year-old female patient with rheumatoid arthritis received disease-modifying agents in various combinations for 9 years. Due to unresponsiveness to treatment, the biological agent rituximab was initiated. The patient also had euthyroided Hashimoto’s thyroiditis and nodular goiter for 15 years. At the time of the diagnosis of Hashimoto thyroiditis, anti-thyroid peroxidase (anti-TPO): 45 IU/mL (0-35), anti-thyroglobulin (anti-Tg) >3000 IU/mL (0-115) but after 4 cycles of treatment with rituximab anti-TPO: 7.38 U/mL (0-35), anti-Tg

Objective: Hashimoto’s thyroiditis (HT) is the most common autoimmune thyroid disease. There are studies suggesting that childhood traumas cause hypothalamic-pituitary-adrenal axis dysfunction in adulthood, which predisposes patients to autoimmune diseases. Our study aimed to investigate the relationship between HT and childhood trauma. Methods: In our study, we included 52 patients diagnosed with HT and 31 healthy controls and evaluated the Turkish Childhood Trauma Questionnaire (which evaluates childhood traumas retrospectively) in both groups. The diagnosis of HT was confirmed using anti-thyroid peroxi-dase (anti-TPO) levels and thyroid ultrasonography. Results: The childhood emotional neglect score (10.79±3.90) was significantly higher in pa-tients with HT than in the control group (p=0.04). However, no significant difference was ob-served between the two groups regarding other components. In addition, a significant positive correlation was found between anti-TPO levels and emotional neglect score (p=0.02; r=0.26). Conclusion: The significantly higher emotional neglect score in patients with HT compared with the control group and the positive correlation between childhood emotional neglect score and anti-TPO level suggest that childhood traumas may play a role in the etiology of adult HT. Further and large-scale studies are needed to elucidate all aspects of this subject.

Objective: Many studies are interested in the association between non-alcoholic fatty liver disease (N-AFLD) and other parameters. Our study evaluated the association between serum uric acid (SrUA) levels and N-AFLD in non-diabetic non-obese adults. Methods: In this study, 50 patients and 50 control subjects were enrolled to investigate the association between SrUA and N-AFLD in adults. The Kruskal-Wallis test was used to compare SrUA values according to ultrasonographic liver fat levels. Results: A statistically significant difference was found between the N-AFLD and control subjects according to the mean SrUA level (p

Emotion recognition is a crucial aspect of human–computer interaction, particularly in the field of marketing and advertising. Call centers play a vital role in generating positive client experiences and maintaining relationships. As individuals increasingly rely on computers for daily tasks, there is a growing need to improve human–computer interactions. Research has been conducted on emotion recognition, in three main areas: facial expression-based, voice-based, and text-based. This study focuses on emotion recognition on incoming customer calls to call centers, which plays a vital role in customer experience and company satisfaction. The study uses real-life customer data provided by Turkish Mobile Operators to analyze the customer’s emotional state and inform call center employees about the emotional state. The model created in this research is a significant milestone for sentiment analysis in the Turkish language, demonstrating the ability to acquire fundamental patterns and categorize emotional expressions. The objective is to analyze the emotional condition of individuals using audio data received from phone calls, focusing on identifying good, negative, and neutral emotional states. Deep learning techniques are employed to analyze the results, with an accuracy value of 0.91, which is acceptable for our partner the “Turkcell Global Bilgi Pazarlama Danışmanlık ve Çağrı Servisi Hizmetleri” Incorporation.

One of the most challenging and common problems in machine learning is the Feature Selection (FS) process, which reduces the dataset size by finding optimal subsets of features. The Horse Herd Optimization Algorithm (HOA) is a new metaheuristic algorithm created by modeling the herd behavior of horses and developed for large scale optimization problems. This paper proposes the binary version of the HOA as a wrapper FS method to solve the FS problem. The proposed algorithm is a binary chaotic horse herd optimization algorithm for feature selection (BCHOAFS). The proposed BCHOAFS is applied to select the optimal feature combination that maximizes classification accuracy while minimizing the number of selected features. Classifier algorithms from machine learning algorithms were used to test the accuracy of the reduced subsets. The proposed method was named binary horse herd optimization for feature selection (BHOAFS) before adding chaotic maps; the k-nearest neighbor (k-NN) and Support Vector Machine (SVM) were tested as separate classifiers. It has been seen that k-NN classification accuracy gives better results than SVM. The BHOAFS-kNN method using the k-NN classification was combined with five chaotic maps and named as BCHOAFS-Logistics, BCHOAFS-Piecewise, BCHOAFS-Singer, BCHOAFS-Sinusoidal, BCHOAFS-Tent. The BCHOAFS versions were run on datasets consisting of 18 different sizes and quality datasets (i.e., low scale, medium scale, and large scale) taken from the UCI repository and compared with state-of-the-art algorithms in previous studies. The results prove that the proposed version, especially with the BCHOAFS-Piecewise and the BCHOAFS-Singer chaotic map outperforms or competes with well-known methods. The proof of the proposed approach’s statistical significance has been validated using the Friedman Signed Rank test and post hoc Wilcoxon test. The novelty of BCHOAFS is that HOA, which is an optimization algorithm specially designed for large scale data, is the first binary chaotic-based algorithm developed for feature selection problems. It also proposes a new local search strategy called Similarity Measurement Function (SMF). As a result, versions of the proposed algorithm BCHOAFS can be used for the FS problem.

Arrays of Cholesteric Spherical Reflectors (CSRs), microscopic cholesteric liquid crystals in a spherical shape, have been argued to become a game-changing technology in anti-counterfeiting. Used to build identifiable tags or coating, called CSR IDs, they can supply objects with unclonable fingerprint-like characteristics, making it possible to authenticate objects. In a previous study, we have shown how to extract minutiæ from CSR IDs. In this journal version, we build on that previous research, consolidate the methodology, and test it over CSR IDs obtained by different production processes. We measure the robustness and reliability of our procedure on large and variegate sets of CSR IDs’ images taken with a professional microscope (Laboratory Data set) and with a microscope that could be used in a realistic scenario (Realistic Data set). We measure intra-distance and interdistance, proving that we can distinguish images coming from the same CSR ID from images of different CSR IDs. However, without surprise, images in Laboratory Data set have an intra-distance that on average is less, and with less variance, than the intra-distance between responses from Realistic Data set. With this evidence, we discuss a few requirements for an anti-counterfeiting technology based on CSRs.

In this paper we present effect of the chaotic crossover operator with different chaotic maps on the metaheuristic search algorithm Breeding Swarms algorithm which is the Particle Swarm Optimization’s one of the genetic algorithm hybrid form. Some of the many optimization problems could have too many local extrema. Most of the time optimization algorithms could stuck on these extrema therefore these algorithms could have trouble with finding global extremum. To avoiding local extrema and conduct better search on search space, a chaotic number generator is used on Breeding Swarms algorithm’s most of the random procedures. To test efficiency and randomness of the chaotic crossover operator, different chaotic maps are used on the Breeding Swarm algorithm. Test and performance evaluations are conducted on Multimodal and unimodal benchmark functions. This new approach showed us that modified Breeding Swarms algorithm yielded slightly better results than Particle Swarm Optimization and original Breeding Swarms algorithms on tested benchmark functions.

Introduction:Patients with polycystic ovary syndrome (PCOS) are in the risk group for early-onset cardiovascular disease. There are few studies evaluating physiological and inflammatory cardiovascular risk factors in PCOS. Our study aimed to measure carotid intima-media thickness (IMT) in PCOS cases and to assess the effects of metformin, ethinyl estradiol/cyproterone acetate (EE/CA) and metformin + EE/ CA combination therapy on carotid IMT, insulin resistance, C-reactive protein (CRP), apelin and adiponectin.Methods:Basal carotid IMT, insulin resistance [Homeostasis model assessment insulin resistance (HOMA-IR)], apelin, adiponectin, and CRP values were evaluated in 60 women with PCOS and 43 healthy volunteers between the ages of 18 and 45. After baseline evaluation, patients were divided into metformin (n=20), EE/CA (n=20) and metformin + EE/CA (n=20) treatment groups. Treatment regimens were administered for six months. At the end of the treatment, the same parameters were re-evaluated.Results:Compared with the control group, CRP (p=0.003), HOMA-IR (p=0.004) and IMT (p=0.049) were significantly higher, and adiponectin (p=0.002) and apelin (p=0.031) levels were significantly lower in patients with PCOS. At the end of the six-month treatment, the adiponectin level in the metformin (p=0.012) and metformin + EE/CA groups (p=0.012), and the apelin level in the metformin (p=0.024), EE/CA (p=0.024) and metformin + EE/CA groups (p=0.024) were significantly higher. There was no statistically significant change in CRP level in all treatment groups (p>0.05). There was no statistically significant change in carotid IMT value in all treatment groups (p>0.05).Conclusion:According to these results, we can say that women with PCOS have subclinical atherosclerosis and that metformin treatment has a positive effect on subclinical atherosclerosis.

Üretici firmaların çoğu için, &nbspgelen siparişler doğrultusunda üretimin planlanması ve kontrolü oldukça zordur. Firmalar, bu planlama ve kontrolü yaparken, hammadde veya malzemenin girişinden, son ürünün dağıtımına kadar bir çok süreci değerlendirmek durumundadırlar. Bu değerlendirme işlemleri, karar desteği sağlayan bilgisayar yazılımları ile daha hızlı ve doğru biçimde yapılabilmektedir. Teknolojinin yükselen trendi olan mobil destekli uygulamalar da, müşterilerin sipariş alışkanlıklarında değişikliklere yol açmıştır. Bu çalışmada, müşteriden mobil tabanlı gelen siparişler doğrultusunda tasarım ve üretim yapan imalat firmaları için hazırlanan ve siparişlerin zamanında karşılanabilmesini amaçlayan bir karar destek sistemi tanıtılmaktadır.

The desire of companies to establish strong control mechanisms due to economic fluctuations and changes in our country and in the world, and the efforts of fast-growing companies to institutionalize and to make their growth stable and sustainable have made the establishment of an internal control system a requirement. According to the data of the Union of Insurance and Reinsurance Companies of Turkey, the insurance sector has grown by 14.9% in 2017. 64.2% of the insurance activities in our country are made through insurance agencies. In order for the growth in the insurance sector to be stable and sustainable, it is essential for insurance agencies to establish their own internal control systems and to maintain their sustainable effectiveness. In this study, the internal control system and the matter of ensuring sustainable effectiveness were researched by using the interview and observation method in an insurance agency operating in 200 different locations in Turkey. The insurance agency, which was subject of the study, is one of the largest insurance agencies in Turkey in terms of premium production, number of personnel, sales channel distribution and organizational structure. The findings and expectations in the researched insurance agency serve as the scientific data for the other agencies operating in the insurance sector, when the fact that the other insurance agencies have similar structures with the researched insurance agency, and it is being mandatory to establish internal control systems in insurance agencies, the size of the researched insurance agency and the risks in insurance sector are taken into consideration.

Background: Diabetic ketoacidosis (DKA) is a potentially life-threatening complication of diabetes mellitus and can lead to death if untreated. It is a complex metabolic state characterised by hyperglycaemia, acidosis and ketonuria. Bonsai is one of the herbal incense products that contains synthetic cannabinoid and can be easily accessible via the internet in many countries. It cannot be detected in blood and urine studies using conventional methods. Synthetic cannabinoid abuse is associated with severe side effects, including tachycardia, high blood pressure, acidosis, excess sedation and coma. Case Report: A 17-year-old male patient was brought to the emergency department with sudden onset of dyspnoea. Laboratory investigations revealed hyperglycaemia, acidosis and ketonuria. He was admitted to the intensive care unit with a diagnosis of diabetic ketoacidosis. He was not considered a typical case of diabetic ketoacidosis because of the tendency to hypokalaemia, persistent tachycardia and bronchoscopic findings. We learned from his friends that he had used cannabis for a week and used bonzai on the day that he was brought to the emergency service. Conclusion: Diabetic ketoacidosis with prolonged acidosis and tendency to hypokalaemia are investigated for the consumption of synthetic cannabinoids.

Businesses today recognize the importance of business performance management (BPM) as an effective business strategy and practical solution to a robust supply chain management process. At the same time, businesses seek to deepen their footprints in global markets, to actively use critical metrics, KPIs (Key Performance Indicators), in business performance management, to make performance management compatible with strategic goals, up-to-date and sustainable. KPIs are priority indicators determined to achieve the strategic objectives of the enterprise. Updating the KPIs used to measure, monitor and analyze business performance also has a critical place in performance management. This article presents a case study of a novel approach to real-time updating and monitoring KPIs integrated into supply chain management (SCM) software. The proposed approach bridges the gap between measuring and implementing business performance. The study analyzes and aligns the relationships of duplicate KPIs. It systematically carries out the KPI weights of the managers in line with the strategic goals and improves performance management by eliminating the weakness in the KPI change. It also provides a framework for sustainable performance management and discusses the case study with implications of KPIs that affect performance management success.

Over the last decade, genome-scale metabolic models have been increasingly used to study plant metabolic behaviour at the tissue and multi-tissue level under different environmental conditions. Quercus suber, also known as the cork oak tree, is one of the most important forest communities of the Mediterranean/Iberian region. In this work, we present the genome-scale metabolic model of the Q. suber (iEC7871). The metabolic model comprises 7871 genes, 6231 reactions, and 6481 metabolites across eight compartments. Transcriptomics data was integrated into the model to obtain tissue-specific models for the leaf, inner bark, and phellogen, with specific biomass compositions. The tissue-specific models were merged into a diel multi-tissue metabolic model to predict interactions among the three tissues at the light and dark phases. The metabolic models were also used to analyse the pathways associated with the synthesis of suberin monomers, namely the acyl-lipids, phenylpropanoids, isoprenoids, and flavonoids production. The models developed in this work provide a systematic overview of the metabolism of Q. suber, including its secondary metabolism pathways and cork formation.