Search results for: item bias

Authors: Hamzeh Dodeen

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This study aims at examining the effects of item wording effects on the factor structure of the University of California, Los Angeles (UCLA) Loneliness Scale: gender, age, and marital status differences. A total of 2374 persons from the UAE participated, representing six different populations (teenagers/elderly, males/females, and married/unmarried). The results of the exploratory factor analysis using principal axis factoring with (oblique) rotation revealed that two factors were extracted from the 20 items of the scale. The nine positively worded items were highly loaded on the first factor, while 10 out of the 11 negatively worded items were highly loaded on the second factor. The two-factor solution was confirmed on the six different populations based on age, gender, and marital status. It has been concluded that the rating of the UCLA scale is affected by a response style related to the item wording.

Keywords: UCLA Loneliness Scale, loneliness, positively worded items, factor structure, negatively worded items

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Authors: Hina Iqbal, Mustansar Ali Ghazanfar, Sandor Szedmak

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Recommender systems uses artificial intelligence practices for filtering obscure information and can predict if a user likes a specified item. Kernel mapping Recommender systems have been proposed which are accurate and state-of-the-art algorithms and resolve recommender system’s design objectives such as; long tail, cold-start, and sparsity. The aim of research is to propose hybrid framework that can efficiently integrate different versions— namely item-based and user-based KMR— of KMR algorithm. We have proposed various heuristic algorithms that integrate different versions of KMR (into a unified framework) resulting in improved accuracy and elimination of problems associated with conventional recommender system. We have tested our system on publically available movies dataset and benchmark with KMR. The results (in terms of accuracy, precision, recall, F1 measure and ROC metrics) reveal that the proposed algorithm is quite accurate especially under cold-start and sparse scenarios.

Keywords: Kernel Mapping Recommender Systems, hybrid recommender systems, cold start, sparsity, long tail

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Authors: Kevin Zhao, Norman J. Horing

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A methodology for cells sorting and circulating tumor cell detection and discrimination is presented in this paper. The technique is based on Dielectrophoresis and microfluidic device theory. Specifically, the sorting of the cells is realized by adjusting the relation among the sedimentation forces, the drag force provided by the fluid, and the Dielectrophortic force that is relevant to the bias voltage applied on the device. The relation leads to manipulation of the elevation of the cells of the same kind to a height by controlling the bias voltage. Once the cells have been lifted to a position next to the bottom of the cell collection channel, the buffer fluid flashes them into the cell collection channel. Repeated elevation of the cells leads to a complete sorting of the cells in the sample chamber. A proof-of-principle example is presented which verifies the feasibility of the methodology.

Keywords: cell sorter, CTC cell, detection and discrimination, dielectrophoresisords, simulation

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Authors: Yuri Boiko, Iluju Kiringa, Tet Yeap

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We use modeling and simulation tools, to introduce a novel bias injection attack, named the ’Induced Pulsation Attack’, which targets Cyber Physical Systems with closed-loop controlled Brushless DC (BLDC) motor and Kalman filter driver in the feedback loop. This attack involves engaging a linear function with a constant gradient to distort the coefficient of the injected bias, which falsifies the Kalman filter estimates of the rotor’s angular speed. As a result, this manipulation interaction inside the control system causes periodic pulsations in a form of asymmetric sine wave of both current and voltage in the circuit windings, with a high magnitude. It is shown that by varying the gradient of linear function, one can control both the frequency and structure of the induced pulsations. It is also demonstrated that terminating the attack at any point leads to additional compensating effort from the controller to restore the speed to its equilibrium value. This compensation effort produces an exponentially decaying wave, which we call the ’attack withdrawal syndrome’ wave. The conditions for maximizing or minimizing the impact of the attack withdrawal syndrome are determined. Linking the termination of the attack to the end of the full period of the induced pulsation wave has been shown to nullify the attack withdrawal syndrome wave, thereby improving the attack’s covertness.

Keywords: cyber-attack, induced pulsation, bias injection, Kalman filter, BLDC motor, control system, closed loop, P- controller, PID-controller, saw-function, cyber-physical system

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Authors: Suddhasil Siddhanta, Debasish Nandy

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Child sex ratios pattern in the Asian Population is highly masculine mainly due to birth masculinity and gender bias in child mortality. The vast and the growing literature of female deficit in world population points out the diffusion of child sex ratio pattern in many Asian as well as neighboring European countries. However, little attention has been given to understand the common factors in different demographics in explaining child sex ratio pattern. Such a scholarship is extremely important as level of gender inequity is different in different country set up. Our paper tries to explain the major structural commonalities in the child masculinity pattern in two demographic billionaires - India and China. The analysis reveals that apart from geographical diffusion of sex selection technology, patrilocal social structure, as proxied by households with more than one generation in China and proportion of population aged 65 years and above in India, can explain significant variation of missing girl child in these two countries. Even after controlling for individual capacity building factors like educational attainment, or work force participation, the measure of social stratification is coming out to be the major determinant of child sex ratio variation. Other socio economic factors that perform much well are the agency building factors of the females, like changing pattern of marriage customs which is proxied by divorce and remarriage ratio for china and percentage of female marrying at or after the age of 20 years in India and the female workforce participation. Proportion of minorities in socio-religious composition of the population and gender bias in scholastic attainment in both these counties are also found to be significant in modeling child sex ratio variations. All these significant common factors associated with child sex ratio point toward the one single most important factor: the historical evolution of patriarchy and its contemporary perpetuation in both the countries. It seems that prohibition of sex selection might not be sufficient to combat the peculiar skewness of excessive maleness in child population in both these countries. Demand sided policies is therefore utmost important to root out the gender bias in child sex ratios.

Keywords: child sex ratios, gender bias, structural factors, prosperity, patrilocality

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Authors: Temesgen Geremew

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ZnO is currently receiving a lot of attention in the semiconductor industry due to its unique characteristics. ZnO is widely used in solar cells, heat-reflecting glasses, optoelectronic bias, and detectors. In this composition, we provide an overview of the ZnO thin flicks' packages, methods of characterization, and implicit operations. They consist of Transmission spectroscopy, Raman spectroscopy, Field emigration surveying electron microscopy, and X-ray diffraction. This review content also demonstrates how ZnO thin flicks function in electrical components for piezoelectric bias, optoelectronics, detectors, and renewable energy sources. Zinc oxide (ZnO) thin films offer a captivating tapestry of possibilities due to their unique blend of electrical, optical, and mechanical properties. This review delves into the realm of their potential applications and future prospects, highlighting the pivotal contributions of research endeavors aimed at tailoring their functionalities.

Keywords: Zinc oxide, raman spectroscopy, thin films, piezoelectric devices

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Authors: Leah Wilck

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Eyewitness identification is arguably one of the most utilized practices within our legal system; however, exoneration cases indicate that this practice may lead to accuracy and conviction errors. The purpose of this study was to examine the effects of the cross-race effect, the phenomena in which people are able to more easily and accurately identify faces from within their racial category, on the accuracy of eyewitness identification. Participants watched three separate videos of a perpetrator trying to steal a bicycle. In each video, the perpetrator was of a different race and gender. Participants watched a video where the perpetrator was a Black male, a White male, and a White female. Following the completion of watching each video, participants were asked to recall everything they could about the perpetrator they witnessed. The initial results of the study did not find the expected cross-race effect impacted the eyewitness identification accuracy. These surprising results are discussed in terms of cross-race bias and recognition theory as well as applied implications.

Keywords: cross race effect, eyewitness identification, own-race bias, racial profiling

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Authors: Antonis Constantinides, Christos Yiallouras, Christakis Damianou

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The application of today's semiconductor transistors in high power UHF DVB-T linear amplifiers has evolved significantly by utilizing LDMOS technology. This fact provides engineers with the option to design a single transistor signal amplifier which enables output power and linearity that was unobtainable previously using bipolar junction transistors or later type first generation MOSFETS. The quiescent current stability in terms of thermal variations of the LDMOS guarantees a robust operation in any topology of DVB-T signal amplifiers. Otherwise, progressively uncontrolled heat dissipation enhancement on the LDMOS case can degrade the amplifier’s crucial parameters in regards to the gain, linearity, and RF stability, resulting in dysfunctional operation or a total destruction of the unit. This paper presents one more sophisticated approach from the traditional biasing circuits used so far in LDMOS DVB-T amplifiers. It utilizes a microprocessor control technology, providing stability in topologies where IDQ must be perfectly accurate.

Keywords: LDMOS, amplifier, back-off, bias circuit

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Authors: Essa Alenazi, Zulfikar Adamu

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The Kingdom of Saudi Arabia (KSA) is not an exception in relying on the growth of its construction industry to support rapid population growth. However, its need for infrastructure development is constrained by low productivity levels and cost overruns caused by factors such as delays to project completion. Delays in delivering a construction project are a global issue and while theories such as Optimism Bias have been used to explain such delays, in KSA, client-related causes of delays are also significant. The objective of this paper is to develop a framework-based approach to explore how the country’s construction industry can manage and reduce delays in construction projects through building information modelling (BIM) in order to mitigate the cost consequences of such delays.  It comprehensively and systematically reviewed the global literature on the subject and identified gaps, critical delay factors and the specific benefits that BIM can deliver for the delay management.  A case study comprising of nine hospital projects that have experienced delay and cost overruns was also carried out. Five critical delay factors related to the clients were identified as candidates that can be mitigated through BIM’s benefits. These factors are: Ineffective planning and scheduling of the project; changes during construction by the client; delay in progress payment; slowness in decision making by the client; and poor communication between clients and other stakeholders. In addition, data from the case study projects strongly suggest that optimism bias is present in many of the hospital projects. Further validation via key stakeholder interviews and documentations are planned.

Keywords: building information modelling (BIM), clients perspective, delay management, optimism bias, public sector projects

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Authors: Alsaidi M. Altaher, Mohd Tahir Ismail

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Wavelet thresholding has been a power tool in curve estimation and data analysis. In the presence of outliers this non parametric estimator can not suppress the outliers involved. This study proposes a new two-stage combined method based on the use of the median filter as primary step before applying wavelet thresholding. After suppressing the outliers in a signal through the median filter, the classical wavelet thresholding is then applied for removing the remaining noise. We use automatic boundary corrections; using a low order polynomial model or local polynomial model as a more realistic rule to correct the bias at the boundary region; instead of using the classical assumptions such periodic or symmetric. A simulation experiment has been conducted to evaluate the numerical performance of the proposed method. Results show strong evidences that the proposed method is extremely effective in terms of correcting the boundary bias and eliminating outlier’s sensitivity.

Keywords: boundary correction, median filter, simulation, wavelet thresholding

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Authors: Kyoung-Jae Kim

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Collaborative Filtering (CF) is a popular technique for the personalization in the E-commerce domain to reduce information overload. In general, CF provides recommending items list based on other similar users’ preferences from the user-item matrix and predicts the focal user’s preference for particular items by using them. Many recommender systems in real-world use CF techniques because it’s excellent accuracy and robustness. However, it has some limitations including sparsity problems and complex dimensionality in a user-item matrix. In addition, traditional CF does not consider the emotional interaction between users. In this study, we propose recommender systems using social network and singular value decomposition (SVD) to alleviate some limitations. The purpose of this study is to reduce the dimensionality of data set using SVD and to improve the performance of CF by using emotional information from social network data of the focal user. In this study, we test the usability of hybrid CF, SVD and social network information model using the real-world data. The experimental results show that the proposed model outperforms conventional CF models.

Keywords: recommender systems, collaborative filtering, social network information, singular value decomposition

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Authors: Xiaohua Zhu, Lingling Ma, Yongguang Zhao

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Leaf Area Index (LAI) is a key structural characteristic of crops and plays a significant role in precision agricultural management and farmland ecosystem modeling. However, LAI retrieved from different resolution data contain a scaling bias due to the spatial heterogeneity and model non-linearity, that is, there is scale effect during multi-scale LAI estimate. In this article, a typical farmland in semi-arid regions of Chinese Inner Mongolia is taken as the study area, based on the combination of PROSPECT model and SAIL model, a multiple dimensional Look-Up-Table (LUT) is generated for multiple crops LAI estimation from unmanned aerial vehicle (UAV) hyperspectral data. Based on Taylor expansion method and computational geometry model, a scale transfer model considering both difference between inter- and intra-class is constructed for scale effect analysis of LAI inversion over inhomogeneous surface. The results indicate that, (1) the LUT method based on classification and parameter sensitive analysis is useful for LAI retrieval of corn, potato, sunflower and melon on the typical farmland, with correlation coefficient R2 of 0.82 and root mean square error RMSE of 0.43m2/m-2. (2) The scale effect of LAI is becoming obvious with the decrease of image resolution, and maximum scale bias is more than 45%. (3) The scale effect of inter-classes is higher than that of intra-class, which can be corrected efficiently by the scale transfer model established based Taylor expansion and Computational geometry. After corrected, the maximum scale bias can be reduced to 1.2%.

Keywords: leaf area index (LAI), scale effect, UAV-based hyperspectral data, look-up-table (LUT), remote sensing

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Authors: Helen Durgante, Mariana F. Sparremberger, Flavia C. Bernardes, Debora D. DellAglio

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Health promotion programmes for retirees, based on Positive Psychology perspectives for the development of strengths and virtues, demand broadened empirical investigation in Brazil. In the case of evidence-based applied research, it is suggested feasibility studies are conducted prior to efficacy trials of the intervention, in order to identify and rectify possible faults in the design and implementation of the intervention. The aim of this study was to evaluate the feasibility of a multicomponent Positive Psychology programme for health promotion of retirees, based on Cognitive Behavioural Therapy and Positive Psychology perspectives. The programme structure included six weekly group sessions (two hours each) encompassing strengths such as Values and self-care, Optimism, Empathy, Gratitude, Forgiveness, and Meaning of life and work. The feasibility criteria evaluated were: Demand, Acceptability, Satisfaction with the programme and with the moderator, Comprehension/Generalization of contents, Evaluation of the moderator (Social Skills and Integrity/Fidelity), Adherence, and programme implementation. Overall, 11 retirees (F=11), age range 54-75, from the metropolitan region of Porto Alegre-RS-Brazil took part in the study. The instruments used were: Qualitative Admission Questionnaire; Moderator Field Diary; the Programme Evaluation Form to assess participants satisfaction with the programme and with the moderator (a six-item 4-point likert scale), and Comprehension/Generalization of contents (a three-item 4-point likert scale); Observers’ Evaluation Form to assess the moderator Social Skills (a five-item 4-point likert scale), Integrity/Fidelity (a 10 item 4-point likert scale), and Adherence (a nine-item 5-point likert scale). Qualitative data were analyzed using content analysis. Descriptive statistics as well as Intraclass Correlations coefficients were used for quantitative data and inter-rater reliability analysis. The results revealed high demand (N = 55 interested people) and acceptability (n = 10 concluded the programme with overall 88.3% frequency rate), satisfaction with the program and with the moderator (X = 3.76, SD = .34), and participants self-report of Comprehension/Generalization of contents provided in the programme (X = 2.82, SD = .51). In terms of the moderator Social Skills (X = 3.93; SD = .40; ICC = .752 [IC = .429-.919]), Integrity/Fidelity (X = 3.93; SD = .31; ICC = .936 [IC = .854-.981]), and participants Adherence (X = 4.90; SD = .29; ICC = .906 [IC = .783-.969]), evaluated by two independent observers present in each session of the programme, descriptive and Intraclass Correlation results were considered adequate. Structural changes were introduced in the intervention design and implementation methods, as well as the removal of items from questionnaires and evaluation forms. The obtained results were satisfactory, allowing changes to be made for further efficacy trials of the programme. Results are discussed taking cultural and contextual demands in Brazil into account.

Keywords: feasibility study, health promotion, positive psychology intervention, programme evaluation, retirees

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Authors: Osiris Terry, Kenneth Hopkinson, Laura Humphrey

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Systematic resampling is the most popularly used resampling method in particle filters. This paper seeks to further the understanding of systematic resampling by defining a formula made up of variables from the sampling equation and the particle weights. The formula is then verified via SPARK, a software verification language. The verified systematic resampling formula states that the minimum/maximum number of possible samples taken of a particle is equal to the floor/ceiling value of particle weight divided by the sampling interval, respectively. This allows for the creation of a randomness spectrum that each resampling method can fall within. Methods on the lower end, e.g., systematic resampling, have less randomness and, thus, are quicker to reach an estimate. Although lower randomness allows for error by having a larger bias towards the size of the weight, having this bias creates vulnerabilities to the noise in the environment, e.g., jamming. Conclusively, this is the first step in characterizing each resampling method. This will allow target-tracking engineers to pick the best resampling method for their environment instead of choosing the most popularly used one.

Keywords: SPARK, software verification, resampling, systematic resampling, particle filter, tracking

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Authors: Wenru Wang

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Over the past decades, Asia has emerged as the ‘diabetes epicentre’ in the world due to rapid economic development, urbanization and nutrition transition. There is an urgent need to develop more effective and cost-effective care management strategies in response to this rising diabetes epidemic. This study aims to develop and compare a nurse-led smartphone-based self-management programme with an existing nurse-led diabetes service on health-related outcomes among type 2 diabetes patients with poor glycemic control in Singapore. We proposed a randomized controlled trial with pre- and repeated post-tests control group design. A total of 128 type 2 diabetes patients with poor glycemic control will be recruited from the diabetes clinic of an acute public hospital in Singapore through convenience sampling. Study participants will be either randomly allocated to the experimental group or control group. Outcome measures used will include the 10-item General Self-Efficacy Scale, 11-item Revised Summary of Diabetes Self-care Activities, and 19-item Diabetes-Dependent Quality of Life. Data will be collected at 3-time points: baseline, three months and six months from the baseline, respectively. It is expected that this programme will be an alternative offered to diabetes patients to master their self-care management skills, in addition to the existing diabetes service provided in diabetes clinics in Singapore hospitals. Also, the self-supporting and less resource-intensive nature of this programme, through the use of smartphone app as a mode of intervention delivery, will greatly reduce nurses’ direct contact time with patients and allow more time to be allocated to those who require more attention. The study has been registered with clinicaltrials.gov. The trial registration number is NCT03088475.

Keywords: type 2 diabetes, poor glycaemic control, nurse-led, smartphone-based, self-management, health-relevant outcomes

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Authors: Torben Hansen, Lars Gronholdt, Alexander Josiassen, Anne Martensen

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Consumers often exhibit a bias in their knowledge; they often think that they know more or less than they do. The concept of 'knowledge over/underconfidence' (O/U) has in previous studies been used to investigate such knowledge bias. O/U appears as a combination of subjective and objective knowledge. Subjective knowledge relates to consumers’ perception of their knowledge, while objective knowledge relates to consumers’ absolute knowledge measured by objective standards. This separation leads to three scenarios: The consumer can either be knowledge calibrated (subjective and objective knowledge are similar), overconfident (subjective knowledge exceeds objective knowledge) or underconfident (objective knowledge exceeds subjective knowledge). Knowledge O/U is a highly useful concept in understanding consumer choice behavior. For example, knowledge overconfident individuals are likely to exaggerate their ability to make right choices, are more likely to opt out of necessary information search, spend less time to carry out a specific task than less knowledge confident consumers, and are more likely to show high financial trading volumes. Through the use of financial services as a case study, this study contributes to previous research by examining how consumer knowledge O/U affects two types of trust (broad-scope trust and narrow-scope trust) and consumer relationship satisfaction. Trust does not only concern consumer trust in individual companies (i.e., narrow.-scope confidence NST), but also concerns consumer confidence in the broader business context in which consumers plan and implement their behavior (i.e., broad scope trust, BST). NST is defined as "the expectation that the service provider can be relied on to deliver on its promises’, while BST is defined as ‘the expectation that companies within a particular business type can generally be relied on to deliver on their promises.’ This study expands our understanding of the interplay between consumer knowledge bias, consumer trust, and relationship marketing in two main ways: First, it is demonstrated that the more knowledge O/U a consumer becomes, the higher/lower NST and levels of relationship satisfaction will be. Second, it is demonstrated that BST has a negative moderating effect on the relationship between knowledge O/U and satisfaction, such that knowledge O/U has a higher positive/negative effect on relationship satisfaction when BST is low vs. high. The data for this study comprises 756 mutual fund investors. Trust is particularly important in consumers’ mutual fund behavior because mutual funds have important responsibilities in providing financial advice and in managing consumers’ funds.

Keywords: knowledge, cognitive bias, trust, customer-seller relationships, financial services

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Authors: Warraichi, G. Kanwal

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The main purpose of the study was to explore relationship between distributive justice and intention to leave the organization by the line staff working in textile sector of Karachi Pakistan. Based on literature review it was hypothesized that perceived distributive justice is positively correlated with intention to leave the organization. A survey of 92 participants (12 female and 80 Male) of textile employee of Karachi was conducted. Two measures were used i.e. 3 item questionnaires on turn over intention developed by Mobley, Horner, & Hollingsworth (1978) and a 13 item and 6 point likert scale questionnaire is adopted from the validated questionnaire of Robert Moorman. Result supports the hypothesis that significant correlation was found between distributive justice and intention to leave the organization. Moreover the results also suggest that distributive justice effect on the intention to leave the organization by the textile line staff. Theoretical and methodological outcome are discussed including recommendations are provided which possibly contribute to the textile industry. Highlighted areas of further study are also provided to open research arena for other researchers.

Keywords: distributive justice, turnover intention, textile industry, Karachi-Pakistan

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Authors: Yi-Lin Chen, Sheng-Jou Hung, Tsunglin Liu

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Adaptive immune system recognizes a wide range of antigens via expressing a large number of structurally distinct T cell and B cell receptor genes. The distinct receptor genes arise from complex rearrangements called V(D)J recombination, and constitute the immune repertoire. A common method of profiling immune repertoire is via amplifying recombined receptor genes using multiple primers and high-throughput sequencing. This multiplex-PCR approach is efficient; however, the resulting repertoire can be distorted because of primer bias. To eliminate primer bias, 5’ RACE is an alternative amplification approach. However, the application of RACE approach is limited by its low efficiency (i.e., the majority of data are non-regular receptor sequences, e.g., containing intronic segments) and lack of the convenient tool for analysis. We propose a computational tool that can correctly identify non-regular receptor sequences in RACE data via aligning receptor sequences against the whole gene instead of only the exon regions as done in all other tools. Using our tool, the remaining regular data allow for an accurate profiling of immune repertoire. In addition, a RACE approach is improved to yield a higher fraction of regular T-cell receptor sequences. Finally, we quantify the degree of primer bias of a multiplex-PCR approach via comparing it to the RACE approach. The results reveal significant differences in frequency of VJ combination by the two approaches. Together, we provide a new experimental and computation pipeline for an unbiased profiling of immune repertoire. As immune repertoire profiling has many applications, e.g., tracing bacterial and viral infection, detection of T cell lymphoma and minimal residual disease, monitoring cancer immunotherapy, etc., our work should benefit scientists who are interested in the applications.

Keywords: immune repertoire, T-cell receptor, 5' RACE, high-throughput sequencing, sequence alignment

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Authors: Fasil Wagnew, Kerri Viney, Kefyalew Addis Alene, Matthew Kelly, Darren Gray

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Background: Undernutrition is a risk factor for tuberculosis (TB), including poor treatment outcomes. However, evidence regarding the effect of undernutrition on TB treatment outcomes is not well understood. We aimed to evaluate the effect of undernutrition on sputum culture conversion and treatment outcomes among people with multi-drug resistance (MDR)-TB. Methods: We searched for publications in the Medline, Embase, Scopus, and Web of Science databases without restrictions on geography or year of publication. We conducted a random-effect meta-analysis to estimate the effects of undernutrition on sputum culture conversion and treatment outcomes. Two reviewers independently assessed the study eligibility, extracted the necessary information, and assessed the risk of bias. Depending on the nature of the data, odds ratio (OR) and hazard ratio (HR) with 95% confidence intervals (CIs) were used to summarize the effect estimates. Potential publication bias was checked using funnel plots and Egger’s tests. Results: Of 2358 records screened, 59 studies comprising a total of 31,254 people with MDR-TB were included. Undernutrition was significantly associated with a lower sputum culture conversion rate (HR 0·7, 95% CI 0·6–0·9, I2=67·1%) and a higher rate of mortality (OR 2·9, 95%CI 2·1–3·8, I2=23·7%) and unfavourable treatment outcomes (OR 1·8, 95%CI 1·5–2·0, I2=72·7%). There was no statistically significant publication bias in the included studies. Three studies were low, forty-two studies were moderate, and fourteen studies were high quality. Interpretations: Undernutrition was significantly associated with unfavourable treatment outcomes, including mortality and lower sputum culture conversion among people with MDR-TB. These findings have implications for supporting targeted nutritional interventions alongside standardised second-line TB drugs.

Keywords: undernutrition, MDR-TB, sputum culture conversion, treatment outcomes, meta-analysis

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Authors: Satish Kumar, Nisha Goyal

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In the stock market, individual investors exhibit different kinds of behaviour. Traditional finance is built on the notion of 'homo economics', which states that humans always make perfectly rational choices to maximize their wealth and minimize risk. That is, traditional finance has concern for how investors should behave rather than how actual investors are behaving. Behavioural finance provides the explanation for this phenomenon. Although finance has been studied for thousands of years, behavioural finance is an emerging field that combines the behavioural or psychological aspects with conventional economic and financial theories to provide explanations on how emotions and cognitive factors influence investors’ behaviours. These emotions and cognitive factors are known as behavioural biases. Because of these biases, investors make irrational investment decisions. Besides, the emotional and cognitive factors, the social influence of media as well as friends, relatives and colleagues also affect investment decisions. Psychological factors influence individual investors’ investment decision making, but few studies have used qualitative methods to understand these factors. The aim of this study is to explore the behavioural factors or biases that affect individuals’ investment decision making. For the purpose of this exploratory study, an in-depth interview method was used because it provides much more exhaustive information and a relaxed atmosphere in which people feel more comfortable to provide information. Twenty investment advisors having a minimum 5 years’ experience in securities firms were interviewed. In this study, thematic content analysis was used to analyse interview transcripts. Thematic content analysis process involves analysis of transcripts, coding and identification of themes from data. Based on the analysis we categorized the statements of advisors into various themes. Past market returns and volatility; preference for safe returns; tendency to believe they are better than others; tendency to divide their money into different accounts/assets; tendency to hold on to loss-making assets; preference to invest in familiar securities; tendency to believe that past events were predictable; tendency to rely on the reference point; tendency to rely on other sources of information; tendency to have regret for making past decisions; tendency to have more sensitivity towards losses than gains; tendency to rely on own skills; tendency to buy rising stocks with the expectation that this rise will continue etc. are some of the major concerns showed by experts about investors. The findings of the study revealed 13 biases such as overconfidence bias, disposition effect, familiarity bias, framing effect, anchoring bias, availability bias, self-attribution bias, representativeness, mental accounting, hindsight bias, regret aversion, loss aversion and herding bias/media biases present in Indian investors. These biases have a negative connotation because they produce a distortion in the calculation of an outcome. These biases are classified under three categories such as cognitive errors, emotional biases and social interaction. The findings of this study may assist both financial service providers and researchers to understand the various psychological biases of individual investors in investment decision making. Additionally, individual investors will also be aware of the behavioural biases that will aid them to make sensible and efficient investment decisions.

Keywords: financial advisors, individual investors, investment decisions, psychological biases, qualitative thematic content analysis

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Authors: Farzana Esmailkassam, Usakorn Kunanuvat, Zahraa Mohammed Ali

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Objective: The key barrier in Clozapine treatment of treatment-resistant schizophrenia (TRS) includes frequent bloods draws to monitor neutropenia, the main drug side effect. WBC and ANC monitoring must occur throughout treatment. Accurate WBC and ANC counts are necessary for clinical decisions to halt, modify or continue clozapine treatment. The CSAN Pronto point-of-care (POC) analyzer generates white blood cells (WBC) and absolute neutrophils (ANC) through image analysis of capillary blood. POC monitoring offers significant advantages over central laboratory testing. This study evaluated the performance of the CSAN Pronto against the Beckman DxH900 Hematology laboratory analyzer. Methods: Forty venous samples (EDTA whole blood) with varying concentrations of WBC and ANC as established on the DxH900 analyzer were tested in duplicates on three CSAN Pronto analyzers. Additionally, both venous and capillary samples were concomitantly collected from 20 volunteers and assessed on the CSAN Pronto and the DxH900 analyzer. The analytical performance including precision using liquid quality controls (QCs) as well as patient samples near the medical decision points, and linearity using a mix of high and low patient samples to create five concentrations was also evaluated. Results: In the precision study for QCs and whole blood, WBC and ANC showed CV inside the limits established according to manufacturer and laboratory acceptability standards. WBC and ANC were found to be linear across the measurement range with a correlation of 0.99. WBC and ANC from all analyzers correlated well in venous samples on the DxH900 across the tested sample ranges with a correlation of > 0.95. Mean bias in ANC obtained on the CSAN pronto versus the DxH900 was 0.07× 109 cells/L (95% L.O.A -0.25 to 0.49) for concentrations <4.0 × 109 cells/L, which includes decision-making cut-offs for continuing clozapine treatment. Mean bias in WBC obtained on the CSAN pronto versus the DxH900 was 0.34× 109 cells/L (95% L.O.A -0.13 to 0.72) for concentrations <5.0 × 109 cells/L. The mean bias was higher (-11% for ANC, 5% for WBC) at higher concentrations. The correlations between capillary and venous samples showed more variability with mean bias of 0.20 × 109 cells/L for the ANC. Conclusions: The CSAN pronto showed acceptable performance in WBC and ANC measurements from venous and capillary samples and was approved for clinical use. This testing will facilitate treatment decisions and improve clozapine uptake and compliance.

Keywords: absolute neutrophil counts, clozapine, point of care, white blood cells

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Authors: Jessica Torres, James W. Sturges

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This correlational study explored the potential relationship between social media use and social connectedness. College students (n = 190) were surveyed using the revised Social Connectedness Scale (SCS-R) and were asked about the number of hours they used social media platforms such as Instagram, TikTok, Twitter, Snapchat, and Facebook. We also developed and administered a 14-item Social Media Use Scale (SMUS) to measure potentially maladaptive social media use, such as use that likely interfered with other activities. The SMUS was found to have good inter-item consistency (Cronbach’s alpha = .92) and was significantly correlated with hours of use, r(182) = .622, p < .001. As expected, we found that the SCS-R scores were inversely related to total hours of social media use, r(182) = -.188 (p < .005). This suggested that lots of time allocated to online interactions is negatively associated with social connectedness in general. Interestingly, however, higher social connectedness scores were associated specifically with Snapchat use, r(28) = .210, p = .004. This may have to do with the specific nature of the Snapchat experience and perhaps its original use for one-to-one communication. The use of other social media platforms (Tiktok, Instagram, Twitter) was not related to better social connectedness scores. Although we failed to find that scores on our measure of problem use (the SMUS) were correlated with social connectedness, we are hopeful that the SMUS will be of use in identifying patterns of maladaptive social media use that may have an impact on other important outcome measures of adaptive functioning and well-being.

Keywords: adaptive functioning, college students, social connectedness, social media use

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Authors: Daniel Marra

Abstract:

This paper analyses from a semantic-diachronic viewpoint the change of meanings that two lexical items of Brazilian-Portuguese language have gone through. Cerrado and Vereda designate currently the second largest Brazilian biome and one of its most important subsystems. Nevertheless, these two words have long individual histories that can be traced back to their Latin etymons. Therefore, the purpose of this work is to highlight the process by which meaning instantiated itself in these words’ formation and to discuss how semantic change installed subsequently in them. As this paper shows, the aforementioned words have been, in different past, synchronizes, created, and undergone changes of meanings by metaphor and metonymy. Besides, it is argued here that semantic change takes place due to external causes, such as generalization and specialization of meaning. It happens when a specialized use of a lexical item, restricted to a particular linguistic group, is adopted by other groups, having its meaning generalized by them. In these processes, the etymological idea of the word is generally lost, which gains, in the new group, less specific meaning in relation to its etymology, sometimes with no relation to the original idea. As a final point, it is claimed that both the creation of a lexical item and its change of meaning involve pragmatic goals, such as the need the language users have to express a new meaning related to a certain reality in the empirical world.

Keywords: Brazilian biomes, metaphor and metonymy, Portuguese lexicon, semantic change

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Authors: Wenjiang Deng, Tian Mou, Yudi Pawitan, Trung Nghia Vu

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Estimation of isoform-level gene expression from RNA-seq data depends on simplifying assumptions, such as uniform reads distribution, that are easily violated in real data. Such violations typically lead to biased estimates. Most existing methods provide a bias correction step(s), which is based on biological considerations, such as GC content–and applied in single samples separately. The main problem is that not all biases are known. For example, new technologies such as single-cell RNA-seq (scRNA-seq) may introduce new sources of bias not seen in bulk-cell data. This study introduces a method called XAEM based on a more flexible and robust statistical model. Existing methods are essentially based on a linear model Xβ, where the design matrix X is known and derived based on the simplifying assumptions. In contrast, XAEM considers Xβ as a bilinear model with both X and β unknown. Joint estimation of X and β is made possible by simultaneous analysis of multi-sample RNA-seq data. Compared to existing methods, XAEM automatically performs empirical correction of potentially unknown biases. XAEM implements an alternating expectation-maximization (AEM) algorithm, alternating between estimation of X and β. For speed XAEM utilizes quasi-mapping for read alignment, thus leading to a fast algorithm. Overall XAEM performs favorably compared to other recent advanced methods. For simulated datasets, XAEM obtains higher accuracy for multiple-isoform genes, particularly for paralogs. In a differential-expression analysis of a real scRNA-seq dataset, XAEM achieves substantially greater rediscovery rates in an independent validation set.

Keywords: alternating EM algorithm, bias correction, bilinear model, gene expression, RNA-seq

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Authors: Baladitya Swaika, Rahul Khatry

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Computer Adaptive Tests (CATs) is one of the most efficient ways for testing the cognitive abilities of students. CATs are based on Item Response Theory (IRT) which is based on item selection and ability estimation using statistical methods of maximum information selection/selection from posterior and maximum-likelihood (ML)/maximum a posteriori (MAP) estimators respectively. This study aims at combining both classical and Bayesian approaches to IRT to create a dataset which is then fed to a neural network which automates the process of ability estimation and then comparing it to traditional CAT models designed using IRT. This study uses python as the base coding language, pymc for statistical modelling of the IRT and scikit-learn for neural network implementations. On creation of the model and on comparison, it is found that the Neural Network based model performs 7-10% worse than the IRT model for score estimations. Although performing poorly, compared to the IRT model, the neural network model can be beneficially used in back-ends for reducing time complexity as the IRT model would have to re-calculate the ability every-time it gets a request whereas the prediction from a neural network could be done in a single step for an existing trained Regressor. This study also proposes a new kind of framework whereby the neural network model could be used to incorporate feature sets, other than the normal IRT feature set and use a neural network’s capacity of learning unknown functions to give rise to better CAT models. Categorical features like test type, etc. could be learnt and incorporated in IRT functions with the help of techniques like logistic regression and can be used to learn functions and expressed as models which may not be trivial to be expressed via equations. This kind of a framework, when implemented would be highly advantageous in psychometrics and cognitive assessments. This study gives a brief overview as to how neural networks can be used in adaptive testing, not only by reducing time-complexity but also by being able to incorporate newer and better datasets which would eventually lead to higher quality testing.

Keywords: computer adaptive tests, item response theory, machine learning, neural networks

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Authors: Wullapa Wongsinlatam

Abstract:

Back propagation algorithm (BP) is a widely used technique in artificial neural network and has been used as a tool for solving the time series problems, such as decreasing training time, maximizing the ability to fall into local minima, and optimizing sensitivity of the initial weights and bias. This paper proposes an improvement of a BP technique which is called IM-COH algorithm (IM-COH). By combining IM-COH algorithm with cuckoo search algorithm (CS), the result is cuckoo search improved control output hidden layer algorithm (CS-IM-COH). This new algorithm has a better ability in optimizing sensitivity of the initial weights and bias than the original BP algorithm. In this research, the algorithm of CS-IM-COH is compared with the original BP, the IM-COH, and the original BP with CS (CS-BP). Furthermore, the selected benchmarks, four time series samples, are shown in this research for illustration. The research shows that the CS-IM-COH algorithm give the best forecasting results compared with the selected samples.

Keywords: artificial neural networks, back propagation algorithm, time series, local minima problem, metaheuristic optimization

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Authors: Shahadut Hossain, Jacek Wesolowski, Zahirul Hoque

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In many epidemiological and environmental studies covariate measurements are subject to the detection limit. In most applications, covariate measurements are usually truncated from below which is known as left-truncation. Because the measuring device, which we use to measure the covariate, fails to detect values falling below the certain threshold. In regression analyses, it causes inflated bias and inaccurate mean squared error (MSE) to the estimators. This paper suggests a response-based regression calibration method to correct the deleterious impact introduced by the covariate detection limit in the estimators of the parameters of simple logistic regression model. Compared to the maximum likelihood method, the proposed method is computationally simpler, and hence easier to implement. It is robust to the violation of distributional assumption about the covariate of interest. In producing correct inference, the performance of the proposed method compared to the other competing methods has been investigated through extensive simulations. A real-life application of the method is also shown using data from a population-based case-control study of non-Hodgkin lymphoma.

Keywords: environmental exposure, detection limit, left truncation, bias, ad-hoc substitution

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Authors: Mohammad Pourmohammadi Fallah, Maziar Salahi

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In the literature, a mixed-integer linear programming model for the integrated production planning and warehouse layout problem is proposed. To solve the model, the authors proposed a Lagrangian relax-and-fix heuristic that takes a significant amount of time to stop with gaps above 5$\%$ for large-scale instances. Here, we present two heuristic algorithms to solve the problem. In the first one, we use a greedy approach by allocating warehouse locations with less reservation costs and also less transportation costs from the production area to locations and from locations to the output point to items with higher demands. Then a smaller model is solved. In the second heuristic, first, we sort items in descending order according to the fraction of the sum of the demands for that item in the time horizon plus the maximum demand for that item in the time horizon and the sum of all its demands in the time horizon. Then we categorize the sorted items into groups of 3, 4, or 5 and solve a small-scale optimization problem for each group, hoping to improve the solution of the first heuristic. Our preliminary numerical results show the effectiveness of the proposed heuristics.

Keywords: capacitated lot-sizing, warehouse layout, mixed-integer linear programming, heuristics algorithm

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Authors: S. Hamid Mirmohammadi, Shahrazad Tamjidzad

Abstract:

This paper is concerned with the single-item continuous review inventory system in which demand is stochastic and discrete. The budget consumed for purchasing the ordered items is not restricted but it incurs extra cost when exceeding specific value. The unit purchasing price depends on the quantity ordered under the all-units discounts cost structure. In many actual systems, the budget as a resource which is occupied by the purchased items is limited and the system is able to confront the resource shortage by charging more costs. Thus, considering the resource shortage costs as a part of system costs, especially when the amount of resource occupied by the purchased item is influenced by quantity discounts, is well motivated by practical concerns. In this paper, an optimization problem is formulated for finding the optimal (R, Q) policy, when the system is influenced by the budget limitation and a discount pricing simultaneously. Properties of the cost function are investigated and then an algorithm based on a one-dimensional search procedure is proposed for finding an optimal (R, Q) policy which minimizes the expected system costs .

Keywords: (R, Q) policy, stochastic demand, backorders, limited resource, quantity discounts

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Authors: Guankai Lin, Wei Tong, Hong Zhu

Abstract:

The electric current induced Joule heating effects have been investigated in La₀.₈Ba₀.₂MnO₃ ultrathin films deposited on LaAlO₃(001) single crystal substrate with smaller lattice constant by using the sol-gel method. By applying moderate bias currents (~ 10 mA), it is found that Joule self-heating simply gives rise to a temperature deviation between the thermostat and the test sample, but the intrinsic ρ(T) relationship measured at a low current (0.1 mA) changes little. However, it is noteworthy that the low-temperature transport behavior degrades from metallic to insulating state after applying higher bias currents ( > 31 mA) in a vacuum. Furthermore, metallic transport can be recovered by placing the degraded film in air. The results clearly suggest that the oxygen vacancy in the La₀.₈Ba₀.₂MnO₃ films is controllable in different atmospheres, particularly with the aid of the Joule self-heating. According to the SEM images, we attribute the controlled oxygen vacancy to the nano-sized labyrinth pattern of the films, where the large surface-to-volume ratio plays a curial role.

Keywords: controlling oxygen vacancy, joule self-heating, manganite, sol-gel method

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