Search results for: depression detection

Authors: Farnoush Haghanipour

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Objective: Father loss as one of the major stress factor, can causethe mental imbalances in children. It's clear that children's family condition of lacking a father is very clearly different from the condition of having a father. The goal of this research is to examine mental imbalances comparative checking in complete form and in five subsidiary categories as aggression, stress and depression, social incompatibility, anti-social behavior, and attention deficit imbalances (wackiness) do between children without father and normal ones. Method: This research is in descriptive and analytical method that reimburse to checking mental imbalances from 50 children that are student in one zone of Rasht’s education and nurture office. Material of this research is RATER behavior questionnaire (teacher form) and data analyses were did by SPSS software. Results: The results showed that there are clear different in relation with behavior imbalances between have father children and children without father and in children without a father behavior imbalance is more. Also showed that there is clearly a difference in aggression, stress, and depression and social incompatibility between children without and without fathers, and in children without a father the proportion increases. However, in antisocial behaviours and attention deficit imbalances there are not a clear difference between them. Conclusion: With upper amount of imbalance behaviour detection in children without fathers compared with children with fathers, it is essential that practitioners of society hygienic and remedy put efforts in order to primary and secondary prevention, for mental health of this group of society.

Keywords: child, behave imbalances, children without father, mental imbalances

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Authors: Yufan Mu

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High salinity process water (HSPW) is often applied in copper ore flotation to alleviate freshwater shortage; however, it is detrimental to copper flotation as it strongly enhances copper activation of pyrite. In this study, the depression effect of a strong oxidiser, potassium ferrate (𝐾₂𝐹₄), on the flotation of copper-activated pyrite was tested to realise the selective separation of pyrite from copper minerals (e.g., chalcopyrite) in flotation using HSPW. The flotation results show that when (𝐾₂𝐹₄) was added in the flotation cell during conditioning, (𝐾₂𝐹₄) could selectively depress copper-activated pyrite while improving chalcopyrite flotation. The depression mechanism of (𝐾₂𝐹₄) on pyrite was ascribed to the significant increase in the pulp potential (Eₕ), dissolved oxygen (DO) concentration and the amount of ferric oxyhydroxides as a result of ferrate decomposition. In the flotation cell, the high Eh and DO concentration promoted the oxidation of low valency metal species (𝐶⁺𝐹e²⁺) released from mineral surfaces and forged steel grinding media, and the resultant high valency metal oxyhydroxides 𝐶u(𝑂H)₂⁄Fe(OH)₃ together with the ferric oxyhydroxides from ferrate decomposition preferentially precipitated on pyrite surface due to its more cathodic nature compared with chalcopyrite, which increased pyrite surface hydrophilicity and reduced its floatability. This study reveals that (𝐾₂𝐹₄) is a highly efficient depressant for pyrite when separating copper minerals from pyrite in flotation using HSPW if dosed properly.

Keywords: copper flotation, pyrite depression, copper-activated pyrite, potassium ferrate, high salinity process water

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Authors: H. N. Cheung

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Self-compassion encourages one to accept oneself, reduce self-criticism and self-judgment, and see one’s shortcomings and setbacks in a balanced view. Adolescent self-compassion is a crucial protective factor against mental illness. It is, however, affected by gender. Given the scarcity of self-compassion scales for adolescents, the current study evaluates the Self-Compassion Scale for Youth (SCS-Y) in a large cross-cultural sample and investigates how the subscales of SCS-Y relate to the dimensions of depressive symptoms across gender. Through the internet-based Qualtrics, a total of 2881 teenagers aged 12 to 18 years were recruited from Hong Kong (HK), China, and the United Kingdom. A Multiple Indicator Multiple Cause (MIMIC) model was used to evaluate measurement invariance of the SCS-Y, and differential item functioning (DIF) was checked across gender. Upon the establishment of the best model, a multigroup structural equation model (SEM) was built between factors of SCS-Y and Multidimensional depression assessment scale (MDAS) which assesses four dimensions of depressive symptoms (emotional, cognitive, somatic and interpersonal). The SCS-Y was shown to have good reliability and validity. The MIMIC model produced a good model fit for a hypothetical six-factor model (CFI = 0.980; TLI = 0.974; RMSEA = 0.038) and no item was flagged for DIF across gender. A gender difference was observed between SCS-Y factors and depression dimensions. Conclusions: The SCS-Y exhibits good psychometric characteristics, including measurement invariance across gender. The study also highlights the gender difference between self-compassion factors and depression dimensions.

Keywords: self compassion, gender, depression, structural equation modelling, MIMIC model

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Authors: Eli Goldstein, David Moore

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The COVID-19 pandemic has brought substantial changes to the lives of college students, impacting them negatively. A consequence of these impacts has led to a significant increase in the negative emotional states of depression, anxiety, and stress, as well as substance use. The present study investigated the relationship between substance use (alcohol, cannabis, nicotine, benzodiazepines, psychedelics, and opioids) among college students from March 2020 to March 2021 and the negative emotional states of depression, anxiety, and stress caused by the COVID-19 pandemic, as well as the relationship between certain personality traits and substance use. Participants (N = 85) answered three questionnaires that measured their expressed symptoms of each negative emotional state, their frequency of substance use, and their levels of five specific personality traits. Investigators predicted that individuals experiencing symptoms of stress and anxiety from the COVID-19 pandemic, as well as individuals showing higher levels of neuroticism and low levels of conscientiousness, would use more depressants (alcohol and benzodiazepines) and opioids to cope with their negative emotional states. Investigators also predicted that individuals who expressed high levels of openness to experience would be more likely to use psychedelics and cannabis to cope with symptoms of depression. Significant correlations showed that individuals primarily used depressants to cope with symptoms of anxiety, as well as cannabis and psychedelics to cope with symptoms of depression. It was also revealed that individuals with higher levels of openness to experience used cannabis and psychedelics, and those with high levels of neuroticism were more likely to use depressants. Two unexpected outcomes appeared for alcohol and depression and depressants and extraversion. Possible explanations for these outcomes are later discussed.

Keywords: substance use, mental health, personality traits, coping strategies

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Authors: Kaveh Shahi, Helmi Z. M. Shafri, Ebrahim Taherzadeh

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In remote sensing, shadow causes problems in many applications such as change detection and classification. It is caused by objects which are elevated, thus can directly affect the accuracy of information. For these reasons, it is very important to detect shadows particularly in urban high spatial resolution imagery which created a significant problem. This paper focuses on automatic shadow detection based on a new spectral index for multispectral imagery known as Shadow Detection Index (SDI). The new spectral index was tested on different areas of World-View 2 images and the results demonstrated that the new spectral index has a massive potential to extract shadows effectively and automatically.

Keywords: spectral index, shadow detection, remote sensing images, World-View 2

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Authors: Nurtazin Sabir, Begon Michael, Yeszhanov Aidyn, Alexander Belyaev, Hughes Nelika, Bethany Levick, Salmurzauly Ruslan

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This paper describes the features of the distribution of the most abundant species of fleas that are carriers of the most dangerous infections in the Balkhash-Alakol depression of Kazakhstan. We show that of 153 species of fleas described in the territory of the great gerbil (Rhombomys opimus Licht.), 35 species are parasitic. 21 of them are specific to gerbils species, and four species of fleas from the Xenopsylla genus are dominant in number and value of epizootic. We also describe the modern features of habitats of these species and their relationship with the great gerbil populations found in the South Balkhash region. It indicates the need for research on the population structure of the most abundant fleas species and their relationship with the structure of the populations of main carrier of transmission infections in the region-great gerbil.

Keywords: Balkhash-Alakol depression, natural foci of plague, species diversity and distribution of fleas, flea and great gerbil population structure, epizootic activity, mass species of fleas

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Authors: Katja Siefken, Astrid Junge

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Background: Research indicates that physical activity (PA) protects us from developing mental disorders. The knowledge regarding optimal domain, intensity, type, context, and amount of PA promotion for the prevention of mental disorders is sparse and incoherent. The objective of this study is to determine the relationship between PA domains and mental well-being, and whether associations vary by domain, amount, context, intensity, and type of PA. Methods: 310 individuals (age: 25 yrs., SD 7; 73% female) completed a questionnaire on personal patterns of their PA behaviour (IPQA) and their mental health (Centre of Epidemiologic Studies Depression Scale (CES-D), Generalized Anxiety Disorder (GAD-7) scale, the subjective physical well-being (FEW-16)). Linear and multiple regression were used for analysis. Findings: Individuals who met the PA recommendation (N=269) reported higher scores on subjective physical well-being than those who did not meet the PA recommendations (N=41). Whilst vigorous intensity PA predicts subjective well-being (β = .122, p = .028), it also correlates with depression. The more vigorously physically active a person is, the higher the depression score (β = .127, p = .026). The strongest impact of PA on mental well-being can be seen in the transport domain. A positive linear correlation on subjective physical well-being (β =.175, p = .002), and a negative linear correlation for anxiety (β =-.142, p = .011) and depression (β = -.164, p = .004) was found. Multiple regression analysis indicates similar results: Time spent in active transport on the bicycle significantly lowers anxiety and depression scores and enhances subjective physical well-being. The more time a participant spends using the bicycle for transport, the lower the depression (β = -.143, p = .013) and anxiety scores (β = -.111,p = .050). Conclusions: Meeting the PA recommendations enhances subjective physical well-being. Active transport has a substantial impact on mental well-being. Findings have implications for policymakers, employers, public health experts and civil society. A stronger focus on the promotion and protection of health through active transport is recommended. Inter-sectoral exchange, outside the health sector, is required. Health systems must engage other sectors in adopting policies that maximize possible health gains.

Keywords: active transport, mental well-being, health promotion, psychological disorders

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Authors: Nam-Uk Kim, Sung-Hwan Kim, Tai-Myoung Chung

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Typical security management systems are not suitable for detecting APT attack, because they cannot draw the big picture from trivial events of security solutions. Although SIEM solutions have security analysis engine for that, their security analysis mechanisms need to be verified in academic field. Although this paper proposes merely an architectural model for APT detection, we will keep studying on correlation analysis mechanism in the future.

Keywords: advanced persistent threat, anomaly detection, data mining

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Authors: Yeongyu Choi, Ju H. Park, Ho-Youl Jung

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In this paper, we propose labeling based RANSAC algorithm for lane detection. Advanced driver assistance systems (ADAS) have been widely researched to avoid unexpected accidents. Lane detection is a necessary system to assist keeping lane and lane departure prevention. The proposed vision based lane detection method applies Canny edge detection, inverse perspective mapping (IPM), K-means algorithm, mathematical morphology operations and 8 connected-component labeling. Next, random samples are selected from each labeling region for RANSAC. The sampling method selects the points of lane with a high probability. Finally, lane parameters of straight line or curve equations are estimated. Through the simulations tested on video recorded at daytime and nighttime, we show that the proposed method has better performance than the existing RANSAC algorithm in various environments.

Keywords: Canny edge detection, k-means algorithm, RANSAC, inverse perspective mapping

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Authors: Daniel Walker, Adam Qureshi, David Marchant, Alex Bahrami Balani

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The present study aimed to assess the impact of concussion and physical pain on depression and health-related quality of life. Depressive symptoms were assessed using the Center for Epidemiological Studies' Depression Scale, and scores of health-related quality of life were measured by health-related quality of life short form-12. Data analysis of 67 participants (concussed 32 vs. 35 non-concussed) revealed that (i) 52% were displaying depressive symptoms (concussed 30% vs. non-concussed 22%) (ii) concussion had a significant effect on depressive symptoms when controlling for pain but no effect on the quality of life scores when controlling the same variable (iii) pain had a significant effect on depressive symptoms and quality of life. With this, both concussion and physical pain seem to have a negative impact on mental health; however, individuals may only recognise a reduction in quality of life with increased physical pain, hence a deterioration in mental well-being could be disregarded as a factor of health-related quality of life.

Keywords: depression, quality of life, concussion, physical pain

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Authors: Yasmeen Jamal Alabdallat, Almutazballlah Bassam Qablan, Obada Ahmad Al Jayyousi, Ihdaa Mahmoud Bani Khalaf, Eman E. Alshial

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Background: Bipolar disorder, formerly known as manic depression, is a mental health status that leads to extreme mood swings that include emotional lows (depression) and highs (mania or hypomania). This systematic review and meta-analysis aimed to assess the safety and efficacy of lithium versus valproate among bipolar patients. Methods: A computer literature search of PubMed, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials was conducted from inception until June 2022. Studies comparing lithium versus valproate among bipolar patients were selected for the analysis, and all relevant outcomes were pooled in the meta-analysis using Review Manager Software. Results: 11 Randomized Clinical Trials were included in this meta-analysis with a total of 4159 patients. Our meta showed that lithium was superior to valproate in terms of Young Mania Rating Scale (YMRS) (MD = 0.00 with 95% CI, (-0.55 – 0.55; I2 = 0%), P = 1.00). The results of the Hamilton Depression Rating Scale (HDRS) showed that the overall effect favored the valproate treated group (MD = 1.41 with 95% CI, (-0.15 – 2.67; I2 = 0%), P = 0.03). Concerning the results of the Montgomery-Asberg Depression Rating Scale (MADRS), the results showed that the lithium was superior to valproate (MD = 0.03 with 95% CI, (-0.80 to 0.87; I2 = 40%), P = 0.94). In terms of the sexual side effect, we found that the valproate was superior to lithium (RR 1.19 with 95% CI, (0.74 to 1.91; I2 = 0%), P = 0.47). The lithium-treated group was superior in comparison to valproate treated group in terms of Abnormal Involuntary Movement Scale (AIMS) (MD = -0.03 with 95% CI (-0.38 to 0.32; I2 = 0%), P = 0.87). The lithium was more favorable in terms of Simpson-Agnes scale (MD = -0.40 with 95% CI, (-0.86 to 0.06; I2 = 0%), P = 0.09). The results of the Barnes akathisia scale showed that the overall effect of the valproate was more favorable in comparison to lithium (MD = 0.05 with 95% CI, (-0.12 to 0.22; I2 = 0%), P = 0.57). Conclusion: Our study revealed that on the scales of efficacy Lithium treated group surpassed Valproate treated group in terms of Young Mania Rating Scale (YMRS), Abnormal Involuntary Movement Scale (AIMS) and Simpson-Agnes scale, but valproate surpassed it in Barnes Akathisia scale. Furthermore, on the scales of depression Hamilton Depression Rating Scale (HDRS) showed that the overall effect favored Valproate treated group, but Lithium surpassed valproate in terms of Montgomery-Asberg Depression Rating Scale (MADRS). Valproate surpassed Lithium in terms of sexual side effects.

Keywords: bipolar, mania, bipolar-depression, sexual dysfunction, sexual side effects, treatment

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Authors: Ayten Bakhtiyar Khasayeva

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Lower Kura depression is a part of the South Caspian Basin (SCB), located between the folded regions of the Greater and Lesser Caucasus. The region is characterized by thick sedimentary cover 22 km (SCB up to 30 km), high sedimentation rate, low geothermal gradient (average value corresponds to 2 °C / 100m). There is Quaternary, Pliocene, Miocene and Oligocene deposits take part in geological structure. Miocene and Oligocene deposits are opened by prospecting and exploratory wells in the areas of Kalamaddin and Garabagli. There are 25 mud volcanoes within the territory of the Lower Kura depression, which are the unique source of information about hydrocarbons contenting great depths. During the wells data research, solid erupted products and mud volcano fluids, and according to the geological and thermal characteristics of the region, it was determined that the main phase of the hydrocarbon generation (MK1-AK2) corresponds to a wide range of depths from 10 to 14 km, which corresponds to the Pliocene-Miocene sediments, and to the "oil and gas windows" according to the intended meaning of R0 ≈ 0,65-0,85%. Fluids of mud volcanoes comprise by the following phases - gas, water. Gas phase consists mainly of methane (99%) of heavy hydrocarbons (С2+ hydrocarbons), CO2, N2, inert components He, Ar. The content of the С2+ hydrocarbons in the gases of mud volcanoes associated with oil deposits is increased. Carbon isotopic composition of methane for the Lower Kura depression varies from -40 ‰ to -60 ‰. Water of mud volcanoes are represented by all four genetic types. However the most typical types of water are HCN type. According to the Mg-Li geothermometer formation of mud waters corresponds to the temperature range from 20 °C to 140 °C (PC2). The solid product emissions of mud volcanoes identified 90 minerals and 30 trace elements. As a result geochemical investigation, thermobaric and geological conditions, zone oil and gas generation - the prospect of the Lower Kura depression is projected to depths greater than 10 km.

Keywords: geology, geochemistry, mud volcanoes, petroleum potential

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Authors: Eui Jun Jeong, Hye Rim Lee, Ji Hye Yoo

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Recent studies have verified the significant relationship of user personality with Internet use. However, in game studies, little research has emphasized on the effects of personality traits on game addiction. This study examined whether big five personality traits affect game addiction with control of psychological, social, and demographic factors. Specifically, using data from a survey of 789 game users in Korea, we conducted a regression analysis to see the associations of psychological (loneliness/depression), social (activities with family/friends), self-efficacy (game/general), gaming (daily gaming time/perception), demographic (age/gender), and personality traits (extraversion, neuroticism conscientiousness, agreeableness, & openness) with the degree of game addiction. Results showed that neuroticism increase game addiction with no effect of extraversion on the addiction. General self-efficacy negatively affected game addiction, whereas game self-efficacy increased the degree of game addiction. Loneliness enhanced game addiction while depression showed a negative effect on the addiction. Results and implications are discussed.

Keywords: game addiction, big five personality, social activities, self-efficacy, loneliness, depression

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Authors: Hyun-Koo Kim, Yong-Hun Kim, Soo-Young Suk, Ju H. Park, Ho-Youl Jung

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This paper presents an effective speed hump detection process at the day-time. we focus only on round types of speed humps in the day-time dynamic road environment. The proposed speed hump detection scheme consists mainly of two process as stereo matching and speed hump detection process. Our proposed process focuses to speed hump detection process. Speed hump detection process consist of noise reduction step, data fusion step, and speed hemp detection step. The proposed system is tested on Intel Core CPU with 2.80 GHz and 4 GB RAM tested in the urban road environments. The frame rate of test videos is 30 frames per second and the size of each frame of grabbed image sequences is 1280 pixels by 670 pixels. Using object-marked sequences acquired with an on-vehicle camera, we recorded speed humps and non-speed humps samples. Result of the tests, our proposed method can be applied in real-time systems by computation time is 13 ms. For instance; our proposed method reaches 96.1 %.

Keywords: data fusion, round types speed hump, speed hump detection, surface filter

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Authors: Kun Xu, Yuan Xu, Jia Qiao

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The document detection plays an important role in optical character recognition and text analysis. Because the traditional detection methods have weak generalization ability, and deep neural network has complex structure and large number of parameters, which cannot be well applied in mobile devices, this paper proposes a lightweight Document Corner Detection Network (DCDNet). DCDNet is a two-stage architecture. The first stage with Encoder-Decoder structure adopts depthwise separable convolution to greatly reduce the network parameters. After introducing the Feature Attention Union (FAU) module, the second stage enhances the feature information of spatial and channel dim and adaptively adjusts the size of receptive field to enhance the feature expression ability of the model. Aiming at solving the problem of the large difference in the number of pixel distribution between corner and non-corner, Weighted Binary Cross Entropy Loss (WBCE Loss) is proposed to define corner detection problem as a classification problem to make the training process more efficient. In order to make up for the lack of Dataset of document corner detection, a Dataset containing 6620 images named Document Corner Detection Dataset (DCDD) is made. Experimental results show that the proposed method can obtain fast, stable and accurate detection results on DCDD.

Keywords: document detection, corner detection, attention mechanism, lightweight

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Authors: Jiandong Lv, Xingang Wang, Cuiling Shao

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The rapid development of social media platforms has made it one of the important news sources. While it provides people with convenient real-time communication channels, fake news and rumors are also spread rapidly through social media platforms, misleading the public and even causing bad social impact in view of the slow speed and poor consistency of artificial rumor detection. We propose an end-to-end rumor detection model-TIMF, which captures the dependencies between multimodal data based on the interactive attention mechanism, uses a transformer for cross-modal feature sequence mapping and combines hybrid fusion strategies to obtain decision results. This paper verifies two multi-modal rumor detection datasets and proves the superior performance and early detection performance of the proposed model.

Keywords: hybrid fusion, multimodal fusion, rumor detection, social media, transformer

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Authors: Tondani Mudau, Sherine B. Van Wyk, Zuhayr Kafaar, Janan Dietrich

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Female adolescents residing in a patriarchal society such as South Africa are more inclined to embrace feminine ideologies. Internalizing these ideologies may expose female adolescents to mental health challenges such as depression and anxiety. This study explored whether the internalisation of adolescent femininity ideologies namely, objectified relationship with own body (ORB) and inauthentic self in relationships (ISR) predicted anxiety and depression in late female adolescents at Stellenbosch University. The sample of the study consisted of 1451 (18-24) female undergraduate and postgraduate students enrolled at Stellenbosch University. The mean age of the participants was 20 (SD=1.46), and most participants (39.7%) were first-year students. The study employed a cross-sectional quantitative research design. Data was collected through an online self-completion survey, the survey consisted of three sections, the first section asked biographical questions regarding age, gender, race and family background. The second section measured the internalisation of feminine ideologies by using the adolescent femininity ideology scale which has two subscales namely inauthentic self in relationship with others (ISR) and objectified relationship with one’s own body (ORB). The ISR scale had the Cronbach Alpha of 0.76, and the ORB scale had the Cronbach Alpha of 0.83. The third section measured mental health (depression and anxiety) by using the Hopkins Symptoms 25-checklist which had the Cronbach Alpha of 0.93. Data were analysed through multiple linear regression from IBM SPSS (Statistical Package for the Social Sciences Version 24). The overall results of the multiple linear regression showed that The AFIS combination accounted for 14% for anxiety as measured by the Hopkins Symptoms Checklist R² = .142, F (2, 682) = 56.431, p < .001. The combination also accounted for 24% for depression as measured by the Hopkins Symptoms Checklist R² = .239, F (2, 682) = 106.971, p < .0. The findings in this study affirm the objectification and feminist theory contentions that internalising femininity ideologies (ISR and ORB) predict negative mental health in female adolescents.

Keywords: adolescents, anxiety, depression, feminine ideologies, inauthentic self, mental health, self-objectification, South Africa

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Authors: Seema Singh Parmar, Shweta Chauhan

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Aims & Objectives: To evaluate the presence of various psychiatric disorders in patients reporting with a headache as the only symptom. Methodology: 200 patients with the chief complain of a headache who visited the psychiatric OPD of a tertiary care were investigated. Out of them 50 who had pure psychiatric illness without any other neurological disease were investigated, and their diagnosis was made. Independent sample t-tests were applied to generate results. Results: The most common psychiatric diagnosis seen in the sample was Depression (64%) out of which 47% showed features of Depression with anxious distress. Other psychiatric disorders seen were Generalized Anxiety Disorder, Panic Attacks, Somatic Symptom Disorder and Obsessive Compulsive Disorder. For pure psychiatry, headache related illnesses female to male ratio was 1.64. Conclusion: The increasing frequency of psychiatric disorders among patients who only visit the doctor seeking treat a headache shows the need for better identification of psychiatric disorders because proper diagnosis and target of psychiatric treatment shall give complete relief to the patient’s symptomatology.

Keywords: anxiety disorders, depression, headache, panic attacks

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Authors: Annisa Siu, Ping Zou

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Background: Existent literature addressing Asian American children and adolescents reveals that this population is experiencing rates of depression comparable to those of European American and other ethnic minority youths. Within the last decade, increased attention has been given to Asian American adolescent mental health. Methods: 44 articles were extracted from Pubmed, PsycINFO, EMBASE, and Proquest CINAHL. Data were subject to thematic analyses and categorized into factors under individual, familial, and community levels. Results: Of all the individual factors, age and gender were the most supported in their relationship with depressive symptoms. Likewise, living situations, parent-child relations, peer relations, and broader environmental factors were strongly evidenced. The remaining psychosocial factors faced contrary evidence or were insubstantially addressed in the empirical literature. Discussion: The identified psychosocial factors within this study offer a starting point for future research to examine what factors should be included in formal or informal methods of screening/consultations. Clinicians should aim to understand the cultural influences specific to Asian American adolescents, particularly the central role that family relations may have on their depressive symptoms. Conclusion: Low awareness of culturally linked expressions of psychological distress can lead to misdiagnosis or under-diagnosis of depression in Asian American youth. Further evidence is needed to clarify the relationship of psychosocial factors linked to Asian American adolescent depressive symptoms.

Keywords: adolescent, Asian American, depression, psychosocial factors

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Authors: Jingting Luo, Yong Wang, Ying Wang

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Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

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Authors: Meng Wu, Atif Rahman, Eng Gee, Lim, Jeong Jin Yu, Rong Yan

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Context: The COVID-19 pandemic has had a profound impact on mental health, with increased rates of anxiety and depression observed. Social support, a critical factor in mental well-being, has also undergone significant changes during the pandemic. This study aims to explore the relationship between social support, anxiety, and depression during COVID-19, taking into account various demographic and contextual factors. Research Aim: The main objective of this study is to conduct a comprehensive systematic review and meta-analysis to examine the impact of social support on anxiety and depression during the COVID-19 pandemic. The study aims to determine the consistency of these relationships across different age groups, occupations, regions, and research paradigms. Methodology: A scoping review and meta-analytic approach were employed in this study. A search was conducted across six databases from 2020 to 2022 to identify relevant studies. The selected studies were then subjected to random effects models, with pooled correlations (r and ρ) estimated. Homogeneity was assessed using Q and I² tests. Subgroup analyses were conducted to explore variations across different demographic and contextual factors. Findings: The meta-analysis of both cross-sectional and longitudinal studies revealed significant correlations between social support, anxiety, and depression during COVID-19. The pooled correlations (ρ) indicated a negative relationship between social support and anxiety (ρ = -0.30, 95% CI = [-0.333, -0.255]) as well as depression (ρ = -0.27, 95% CI = [-0.370, -0.281]). However, further investigation is required to validate these results across different age groups, occupations, and regions. Theoretical Importance: This study emphasizes the multifaceted role of social support in mental health during the COVID-19 pandemic. It highlights the need to reevaluate and expand our understanding of social support's impact on anxiety and depression. The findings contribute to the existing literature by shedding light on the associations and complexities involved in these relationships. Data Collection and Analysis Procedures: The data collection involved an extensive search across six databases to identify relevant studies. The selected studies were then subjected to rigorous analysis using random effects models and subgroup analyses. Pooled correlations were estimated, and homogeneity was assessed using Q and I² tests. Question Addressed: This study aimed to address the question of the impact of social support on anxiety and depression during the COVID-19 pandemic. It sought to determine the consistency of these relationships across different demographic and contextual factors. Conclusion: The findings of this study highlight the significant association between social support, anxiety, and depression during the COVID-19 pandemic. However, further research is needed to validate these findings across different age groups, occupations, and regions. The study emphasizes the need for a comprehensive understanding of social support's multifaceted role in mental health and the importance of considering various contextual and demographic factors in future investigations.

Keywords: social support, anxiety, depression, COVID-19, meta-analysis

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Authors: Malihe Shahidan, Azin Madhi, Meisam Shahbaz

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In recent decades, the role of supply chains in sustaining businesses and establishing their superiority in the market has been under focus. The realization of the goals and strategies of a business enterprise is largely dependent on the cooperation of the chain, including suppliers, distributors, retailers, etc. Supply chains can potentially be disrupted by both internal and external factors. In this paper, resilience strategies have been identified and analyzed in three levels: sourcing, producing, and distributing by considering economic depression as a current risk factor for the machine-made rugs industry. In this study, semi-structured interviews for data gathering and thematic analysis for data analysis are applied. Supply chain data has been gathered from seven rug factories before and after the economic depression through semi-structured interviews. The identified strategies were derived from literature review and validated by collecting data from a group of eighteen industry and university experts, and the results were analyzed using statistical tests. Finally, the outsourcing of new products and products in the new market, the development and completion of the product portfolio, the flexibility in the composition and volume of products, the expansion of the market to price-sensitive, direct sales, and disintermediation have been determined as strategies affecting supply chain resilience of machine-made rugs' industry during an economic depression.

Keywords: distribution, economic depression, machine-made rug, outsourcing, production, sourcing, supply chain, supply chain resilience

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Authors: Maher un Nisa, Ahsan Khawaja

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Retinal imaging with Ultra-WideField (UWF) view technology has opened up new avenues in the field of retinal pathology detection. Recent developments in retinal imaging such as Optos California Imaging Device helps in acquiring high resolution images of the retina to help the Ophthalmologists in diagnosing and analyzing eye related pathologies more accurately. This paper investigates the acquired retinal details by comparing vessel detection in standard 450 color fundus images with the state of the art 2000 UWF retinal images.

Keywords: color fundus, retinal images, ultra-widefield, vessel detection

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Authors: D. L. Tambe, S. Dighe Nachiket

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Objective: Depression is a common but serious illness and the phenothiazine derivatives shows prominent effect against the depression hence work was undertaken to validate this use scientifically. Material and Methods: Synthesis of phenothiazine derivatives are done by the substitution of various groups, but the basic scheme of synthesis is started with synthesis of 4-(Cyclohexylidene) Benzoic acid using PABA. After that with the further six step of synthesis of 3-(10H-phenothiazin-2-yl)-N, 5-diphenyl-4H-1, 2, 4-triazol-4-amine is done which is final product. Antidepressant activity of all the synthesized compounds was evaluated by despair swim test by using Sprague Dawley Rats. Standard drug imipramine was used as the control. In the despair swim test, all the synthesized derivatives showed antidepressant activity. Results: Among the all phenothiazine derivatives four compounds (6.6-7.2 (14H –phenyl ), 9.43 (1H OH), 8.50 (1H NH phenothiazine),6.85-8.21(14H phenyl), 8.50 (1H NH phenothiazine), 11.82 (1H – OH), 6.6-7.2 (8H –phenyl ), 9.43 (1H OH), 8.50 (1H NH phenothiazine), 4.2 (1H NH) and 6.85-8.21(8H phenyl), 8.50 (1H NH phenothiazine), 3.9 (1H NH) 11.82 (1H – OH) showed significant antidepressant activity comparing with control drug imipramine. Conclusion: Various Novel phenothiazine derivatives show more potent antidepressant activity and it plays more beneficial role in human health for the treatment of depression.

Keywords: antidepressant activities, despair swim test, phenothiazine, Sprague Dawley Rats

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Authors: Sergei Aleinik, Yuri Matveev

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In this paper a novel method for the detection of clipping in speech signals is described. It is shown that the new method has better performance than known clipping detection methods, is easy to implement, and is robust to changes in signal amplitude, size of data, etc. Statistical simulation results are presented.

Keywords: clipping, clipped signal, speech signal processing, digital signal processing

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Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

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Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: network intrusion detection, machine learning, artificial neural network, anomaly detection module

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Authors: Antigoni Panagiotopoulou, Lemonia Ragia

Abstract:

High-resolution satellite images can provide detailed information about change detection on the earth. In the present work, QuickBird images of spatial resolution 60 cm/pixel and WorldView images of resolution 30 cm/pixel are utilized to perform automatic change detection in urban and suburban areas of Crete, Greece. There is a relative time difference of 13 years among the satellite images. Multiindex scene representation is applied on the images to classify the scene into buildings, vegetation, water and ground. Then, automatic change detection is made possible by pixel-per-pixel comparison of the classified multi-temporal images. The vegetation index and the water index which have been developed in this study prove effective. Furthermore, the proposed change detection approach not only indicates whether changes have taken place or not but also provides specific information relative to the types of changes. Experimentations with other different scenes in the future could help optimize the proposed spectral indices as well as the entire change detection methodology.

Keywords: change detection, multiindex scene representation, spectral index, QuickBird, WorldView

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Authors: Ziyu Zhang, Xuanyu Ren, Fei Wu, Qinfei Lu, Yongmei Li, Xinyue Zhi

Abstract:

Introduction: Adolescents experience a critical period of physical and psychological growth. Few studies focus on the influence of sleep hygiene on psychological health from the high school period to freshmen year. Also, the influence of the COVID-19 pandemic has public health significance. Methods: Totally 698 students from high school and college were included in the manuscript, and a cross-sectional procedure was conducted; the objective was to make the epidemiological comparison of the social phobia/depression prevalence and discuss the effects of potential determinants. Results: Psychological problems, including social phobia and depression, are prevalent, especially among high school students, with gender differences. The current results indicated that the association between sleep status and social phobia is most obvious among high school students, while the higher MMR risk was found both for high school social phobia students and college depressive freshmen. Moreover, the interaction between social phobia and depression was also obvious for both populations. Conclusions: Psychological problems, including social phobia and depression, are more prevalent among high school girls when compared with their male and freshmen peers. Important influenced factors for the risk of psychological problems among the two populations were different, but media multitasking status should be paid attention to for both.

Keywords: adolescence, psychological health, epidemiology, social culture

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Authors: Pavel Chmelar, Martin Dobrovolny

Abstract:

Laser projection or laser footprint detection is today widely used in many fields of robotics, measurement, or electronics. The system accuracy strictly depends on precise laser footprint detection on target objects. This article deals with the laser line detection based on the RGB segmentation and the component labeling. As a measurement device was used the developed optical rangefinder. The optical rangefinder is equipped with vertical sweeping of the laser beam and high quality camera. This system was developed mainly for automatic exploration and mapping of unknown spaces. In the first section is presented a new detection algorithm. In the second section are presented measurements results. The measurements were performed in variable light conditions in interiors. The last part of the article present achieved results and their differences between day and night measurements.

Keywords: color segmentation, component labelling, laser line detection, automatic mapping, distance measurement, vector map

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Authors: Hyojin Lim, Cuong Nguyen Khac, Ho-Youl Jung

Abstract:

In this paper, we propose moving object detection method which is helpful for driver to safely take his/her car out of parking lot. When moving objects such as motorbikes, pedestrians, the other cars and some obstacles are detected at the rear-side of host vehicle, the proposed algorithm can provide to driver warning. We assume that the host vehicle is just before departure. Gaussian Mixture Model (GMM) based background subtraction is basically applied. Pre-processing such as smoothing and post-processing as morphological filtering are added.We examine “which color space has better performance for detection of moving objects?” Three color spaces including RGB, YCbCr, and Y are applied and compared, in terms of detection rate. Through simulation, we prove that RGB space is more suitable for moving object detection based on background subtraction.

Keywords: gaussian mixture model, background subtraction, moving object detection, color space, morphological filtering

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