Search results for: interval aerobic training

Authors: Junjira Mahaboon, Anongnard Boonpak, Nattakarn Worrasan, Busma Kama, Mujalin Saikliang, Siripor Dankachatarn

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Rubber wood processing is one of the most important industries in southern Thailand. The process has several safety hazards for example unsafe wood cutting machine guarding, wood dust, noise, and heavy lifting. However, workers’ occupational health and safety measures to promote their behaviors are still limited. This quasi-experimental research was to determine factors affecting workers’ safety behaviors using theory of planned behavior after implementing job safety intervention program. The purposes were to (1) determine factors affecting workers’ behaviors and (2) to evaluate effectiveness of the intervention program. The sample of study was 66 workers from a rubber wood processing factory. Factors in the Theory of Planned Behavior model (TPB) were measured before and after the intervention. The factors of TPB included attitude towards behavior, subjective norm, perceived behavioral control, intention, and behavior. Firstly, Job Safety Analysis (JSA) was conducted and Safety Standard Operation Procedures (SSOP) were established. The questionnaire was also used to collect workers’ characteristics and TPB factors. Then, job safety intervention program to promote workers’ behavior according to SSOP were implemented for a four month period. The program included SSOP training, personal protective equipment use, and safety promotional campaign. After that, the TPB factors were again collected. Paired sample t-test and independent t-test were used to analyze the data. The result revealed that attitude towards behavior and intention increased significantly after the intervention at p<0.05. These factors also significantly determined the workers’ safety behavior according to SSOP at p<0.05. However, subjective norm, and perceived behavioral control were not significantly changed nor related to safety behaviors. In conclusion, attitude towards behavior and workers’ intention should be promoted to encourage workers’ safety behaviors. SSOP intervention program e.g. short meeting, safety training, and promotional campaign should be continuously implemented in a routine basis to improve workers’ behavior.

Keywords: job safety analysis, rubber wood processing workers, safety standard operation procedure, theory of planned behavior

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Authors: Sanath Kumar Shetty, Sanya Sinha, K. Kamalakanth Shenoy

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The posterior reference for the ala tragal line is a cause of confusion, with different authors suggesting different locations as to the superior, middle or inferior part of the tragus. This study was conducted on 200 subjects to evaluate if any correlation exists between the variation of angulation of palatal throat form and the relative parallelism of occlusal plane to ala-tragal line at different tragal levels. A Custom made Occlusal Plane Analyzer was used to check the parallelism between the ala-tragal line and occlusal plane. A lateral cephalogram was shot for each subject to measure the angulation of the palatal throat form. Fisher’s exact test was used to evaluate the correlation between the angulation of the palatal throat form and the relative parallelism of occlusal plane to the ala tragal line. Also, a classification was formulated for the palatal throat form, based on confidence interval. From the results of the study, the inferior part, middle part and superior part of the tragus were seen as the reference points in 49.5%, 32% and 18.5% of the subjects respectively. Class I palatal throat form (41degree-50 degree), Class II palatal throat form (below 41 degree) and Class III palatal throat form (above 50 degree) were seen in 42%, 43% and 15% of the subjects respectively. It was also concluded that there is no significant correlation between the variation in the angulations of the palatal throat form and the relative parallelism of occlusal plane to the ala-tragal line.

Keywords: Ala-Tragal line, occlusal plane, palatal throat form, cephalometry

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Authors: Kan Yu, Khui Hung Lee, Eben Afrifa-Yamoah, Jing Guo, Katrina Harrison, Jack Goldblatt, Nicholas Pachter, Jitian Xiao, Guicheng Brad Zhang

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Background and Significance of the Study: Congenital Heart Defects (CHDs) are the most common malformation at birth and one of the leading causes of infant death. Although the exact etiology remains a significant challenge, epigenetic modifications, such as DNA methylation, are thought to contribute to the pathogenesis of congenital heart defects. At present, no existing DNA methylation biomarkers are used for early detection of CHDs. The existing CHD diagnostic techniques are time-consuming and costly and can only be used to diagnose CHDs after an infant was born. The present study employed a machine learning technique to analyse genome-wide methylation data in children with and without CHDs with the aim to find methylation biomarkers for CHDs. Methods: The Illumina Human Methylation EPIC BeadChip was used to screen the genome‐wide DNA methylation profiles of 24 infants diagnosed with congenital heart defects and 24 healthy infants without congenital heart defects. Primary pre-processing was conducted by using RnBeads and limma packages. The methylation levels of top 600 genes with the lowest p-value were selected and further investigated by using a random forest approach. ROC curves were used to analyse the sensitivity and specificity of each biomarker in both training and test sample sets. The functionalities of selected genes with high sensitivity and specificity were then assessed in molecular processes. Major Findings of the Study: Three genes (MIR663, FGF3, and FAM64A) were identified from both training and validating data by random forests with an average sensitivity and specificity of 85% and 95%. GO analyses for the top 600 genes showed that these putative differentially methylated genes were primarily associated with regulation of lipid metabolic process, protein-containing complex localization, and Notch signalling pathway. The present findings highlight that aberrant DNA methylation may play a significant role in the pathogenesis of congenital heart defects.

Keywords: biomarker, congenital heart defects, DNA methylation, random forest

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Authors: Suraj Mehrotra

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The stock market is a volatile, bustling marketplace that is a cornerstone of economics. It defines whether companies are successful or in spiral. A thorough understanding of it is important - many companies have whole divisions dedicated to analysis of both their stock and of rivaling companies. Linking the world of finance and artificial intelligence (AI), especially the stock market, has been a relatively recent development. Predicting how stocks will do considering all external factors and previous data has always been a human task. With the help of AI, however, machine learning models can help us make more complete predictions in financial trends. Taking a look at the stock market specifically, predicting the open, closing, high, and low prices for the next day is very hard to do. Machine learning makes this task a lot easier. A model that builds upon itself that takes in external factors as weights can predict trends far into the future. When used effectively, new doors can be opened up in the business and finance world, and companies can make better and more complete decisions. This paper explores the various techniques used in the prediction of stock prices, from traditional statistical methods to deep learning and neural networks based approaches, among other methods. It provides a detailed analysis of the techniques and also explores the challenges in predictive analysis. For the accuracy of the testing set, taking a look at four different models - linear regression, neural network, decision tree, and naïve Bayes - on the different stocks, Apple, Google, Tesla, Amazon, United Healthcare, Exxon Mobil, J.P. Morgan & Chase, and Johnson & Johnson, the naïve Bayes model and linear regression models worked best. For the testing set, the naïve Bayes model had the highest accuracy along with the linear regression model, followed by the neural network model and then the decision tree model. The training set had similar results except for the fact that the decision tree model was perfect with complete accuracy in its predictions, which makes sense. This means that the decision tree model likely overfitted the training set when used for the testing set.

Keywords: machine learning, testing set, artificial intelligence, stock analysis

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Authors: Neeta Khurana, Ritu Sharma

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This paper is an impact assessment study of the rehabilitation work done for Chhara women in the rural precincts of Ahmedabad. The Chharas constitute a denotified tribe and live in abject poverty. The women of this community are infamous absconders of law and active bootleggers of locally made liquor. As part of a psychological study with a local NGO, the authors headed a training program aimed at rehabilitating and providing these women alternate modes of employment, thereby driving them away from a life of crime. The paper centers on the idea of women entrepreneurship and women empowerment. It notes the importance of handholding in a conflict situation. Most of the research on Chharas is either focused on victimising them for state-sponsored violence or mostly makes a plea on reconditioning them in the mainstream. Going against this trend, this paper which documents the study argues that making these poor women self-dependent is a panacea for their sluggish development. The alienation caused due to the demonisation of the community has made them abandon traditional modes of employment. This has further led the community astray into making illegal country liquor causing further damage to their reputation. Women are at the centre of this vicious circle facing much repression and ostracisation. The study conducted by the PDPU team was an attempt to change this dogmatic alienation of these poor women. It was found that with consistent support and reformist approach towards law, it is possible to drive these women away from a life of penury repression and crime. The aforementioned study uses empirical tools to verify this claim. Placed at the confluence of the sociology of gender and psychology, this paper is a good way to argue that law enforcement cannot be effective without sensitisation to the ground realities of conflict. The study conducted from which the paper borrows was a scientific survey focused on markers of gender and caste realities of the Chharas. The paper mentions various dynamics involved in the training program that paved the way for the successful employment of the women. In an attempt to explain its uniqueness, the paper also has a section on comparing similar social experiments.

Keywords: employment, gender, handholding, rehabilitation

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Authors: Morten Stigaard Laursen, Rasmus Nyholm Jørgensen, Henrik Skov Midtiby, Anders Krogh Mortensen, Sanmohan Baby

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This work contributes a statistical model and simulation framework yielding the best estimate possible for the potential herbicide reduction when using the MoDiCoVi algorithm all the while requiring a efficacy comparable to conventional spraying. In June 2013 a maize field located in Denmark were seeded. The field was divided into parcels which was assigned to one of two main groups: 1) Control, consisting of subgroups of no spray and full dose spraty; 2) MoDiCoVi algorithm subdivided into five different leaf cover thresholds for spray activation. In addition approximately 25% of the parcels were seeded with additional weeds perpendicular to the maize rows. In total 299 parcels were randomly assigned with the 28 different treatment combinations. In the statistical analysis, bootstrapping was used for balancing the number of replicates. The achieved potential herbicide savings was found to be 70% to 95% depending on the initial weed coverage. However additional field trials covering more seasons and locations are needed to verify the generalisation of these results. There is a potential for further herbicide savings as the time interval between the first and second spraying session was not long enough for the weeds to turn yellow, instead they only stagnated in growth.

Keywords: herbicide reduction, macrosprayer, weed crop discrimination, site-specific, sprayer boom

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Authors: Mane Varosyan, Diana Tumanyan, Agnesa Martirosyan

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There are many catastrophic events that end with dire consequences, and to avoid them, people should be well-armed with the necessary information about these situations. During the last years, Serious Games have increasingly gained popularity for training people for different types of emergencies. The major discussed problem is the usage of gamification in education. Moreover, it is mandatory to understand how and what kind of gamified e-learning modules promote engagement. As the theme is emergency, we also find out people’s behavior for creating the final approach. Our proposed solution is an educational video game, “EZZRA”.

Keywords: gamification, education, emergency, serious games, game design, virtual reality, digitalisation

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Authors: Yanting Cao, Kazumitsu Nawata

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As smartphones upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described as more refined, complex, and detailed. In this context, we analyzed a set of experimental data obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model becomes extremely challenging. After a series of feature selection and parameters adjustment, a well-performed SVM classifier has been trained.

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

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Authors: Liang Cheng Chang, Wei Ju Huang, You Cheng Chen

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Investigation and research are keys for conjunctive use of surface and groundwater resources. The hydrogeological structure is an important base for groundwater analysis and simulation. Traditionally, the hydrogeological structure is artificially determined based on geological drill logs, the structure of wells, groundwater levels, and so on. In Taiwan, groundwater observation network has been built and a large amount of groundwater-level observation data are available. The groundwater level is the state variable of the groundwater system, which reflects the system response combining hydrogeological structure, groundwater injection, and extraction. This study applies analytical tools to the observation database to develop a methodology for the identification of confined and unconfined aquifers. These tools include frequency analysis, cross-correlation analysis between rainfall and groundwater level, groundwater regression curve analysis, and decision tree. The developed methodology is then applied to groundwater layer identification of two groundwater systems: Zhuoshui River alluvial fan and Pingtung Plain. The abovementioned frequency analysis uses Fourier Transform processing time-series groundwater level observation data and analyzing daily frequency amplitude of groundwater level caused by artificial groundwater extraction. The cross-correlation analysis between rainfall and groundwater level is used to obtain the groundwater replenishment time between infiltration and the peak groundwater level during wet seasons. The groundwater regression curve, the average rate of groundwater regression, is used to analyze the internal flux in the groundwater system and the flux caused by artificial behaviors. The decision tree uses the information obtained from the above mentioned analytical tools and optimizes the best estimation of the hydrogeological structure. The developed method reaches training accuracy of 92.31% and verification accuracy 93.75% on Zhuoshui River alluvial fan and training accuracy 95.55%, and verification accuracy 100% on Pingtung Plain. This extraordinary accuracy indicates that the developed methodology is a great tool for identifying hydrogeological structures.

Keywords: aquifer identification, decision tree, groundwater, Fourier transform

Procedia PDF Downloads 148

Authors: Tanveer Hussain, Khan Muhammad, Amin Ullah, Mi Young Lee, Sung Wook Baik

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The Big Data generated from distributed vision sensors installed on large scale in smart cities create hurdles in its efficient and beneficial exploration for browsing, retrieval, and indexing. This paper presents a three-folded framework for effective video summarization of such data and provide a compact and representative format of Big Video Data. In the first fold, the paper acquires input video data from the installed cameras and collect clues such as type and count of objects and clarity of the view from a chunk of pre-defined number of frames of each view. The decision of representative view selection for a particular interval is based on fuzzy inference system, acquiring a precise and human resembling decision, reinforced by the known clues as a part of the second fold. In the third fold, the paper forwards the selected view frames to the summary generation mechanism that is supported by a saliency-aware convolution neural network (CNN) model. The new trend of fuzzy rules for view selection followed by CNN architecture for saliency computation makes the multi-view video summarization (MVS) framework a suitable candidate for real-world practice in smart cities.

Keywords: big video data analysis, fuzzy logic, multi-view video summarization, saliency detection

Procedia PDF Downloads 175

Authors: Hsin-Chieh Lee, Fen-Ling Kuo, Jui-Chi Lin

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Background: Upper extremity functional impairment that occurs after stroke includes hemiplegia, synergy movement, muscle hypertonicity, and somatosensory impairment, which result in inefficient and inaccurate movement. Robot-assisted rehabilitation is an intensive training approach that is effective in sensorimotor and hand function recovery. However, these systems mostly focused on the proximal part of the upper limb rather than the distal part. The device used in our study was Gloreha Sinfonia, which focuses on the distal part of the upper limb and uses a dynamic support system to facilitate the whole limb function. The objective of this study was to investigate the effects of robot-assisted therapy (RT) with Gloreha device on sensorimotor, and ADLs in patients with stroke. Method: Patients with stroke (N=25) participated AB or BA (A = 12 RT sessions and B = 12 conventional therapy (CT) sessions) for 6 weeks (60 min at each session, twice a week), with 1-month break for washout period. The performance of the patients was assessed by a blinded assessor at 4 time points (pretest 1, posttest 1, pretest 2, posttest 2) which including the Fugl–Meyer Assessment-upper extremity (FMA-UE), box and block test, electromyography of the extensor digitorum communis (EDC) and brachioradialis, a grip dynamometer for motor evaluation; Semmes–Weinstein hand monofilament and Revision of the Nottingham Sensory Assessment for sensory evaluation; and the Modified Barthel Index (MBI) for assessing the ADL ability. Result: RT group significantly improved FMA-UE proximal scores (p = 0.038), FMA-UE total scores (p = 0.046), and MBI (p = 0.030). The EDC exhibited higher efficiency during the small block grasping task in the RT group than in the CT group (p = 0.050). Conclusions: RT with the Gloreha device might lead to beneficial effects on arm motor function, ADL ability, and EDC muscle recruitment efficacy in patients with subacute to chronic stroke.

Keywords: activities of daily living, hand function, robotic rehabilitation, stroke

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Authors: Igna Brajević Gizdić, Gorka Vuletić

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Introduction: Addiction is a chronic brain relapsing disorder. Opioid Substitution Therapy (OST) using buprenorphine as a medical treatment option shows as a promising option for achieving and maintaining abstinence in opioid-addicted patients. This research aimed to determine and evaluate the quality of life (QoL) in opiate-addicted patients after five years of buprenorphine therapy. Method: The total sample included 44 buprenorphine-maintained opiate addicts in outpatient treatment. The participants were administered the QoL questionnaire (WHOQOL-BREF) at two-time points (T1 and T2) with an interval of at least five years. WHOQOL-BREF contains a total of 26 questions. The first two questions, related to overall QoL and general health status, and the remaining questions (3–26), which represented four domains—physical, psychological, social, and environmental health—were evaluated separately. Results: The results indicated no significant differences in overall self-assessed QoL nor in individual domains after five years (T2) of abstinence with OST buprenorphine- maintenance. Conclusion: These findings indicated no improvement in QoL of buprenorphine-maintenance opiate addicts in outpatient treatment. However, this might be due to the smaller sample size and participants' overall high scores in QoL at T1. This study suggests the importance of expectations when considering the QoL and general health of buprenorphine-maintenance opiate addicts in outpatient treatment.

Keywords: abstinence, addicts, buprenorphine, opioid substitution therapy, quality of life

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Authors: Madrine King'endo

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This study dealt with the influence of spelling errors on English language performance among learners with dysgraphia in public primary schools in West Embu, Embu County, Kenya. The study purposed to investigate the influence of spelling errors on the English language performance among the class three pupils with dysgraphia in public primary schools. The objectives of the study were to identify the spelling errors that learners with dysgraphia make when writing English words and classify the spelling errors they make. Further, the study will establish how the spelling errors affect the performance of the language among the study participants, and suggest the remediation strategies that teachers could use to address the errors. The study could provide the stakeholders with relevant information in writing skills that could help in developing a responsive curriculum to accommodate the teaching and learning needs of learners with dysgraphia, and probably ensure training of teachers in teacher training colleges is tailored within the writing needs of the pupils with dysgraphia. The study was carried out in Embu county because the researcher did not find any study in related literature review concerning the influence of spelling errors on English language performance among learners with dysgraphia in public primary schools done in the area. Moreover, besides being relatively populated enough for a sample population of the study, the area was fairly cosmopolitan to allow a generalization of the study findings. The study assumed the sampled schools will had class three pupils with dysgraphia who exhibited written spelling errors. The study was guided by two spelling approaches: the connectionist stimulation of spelling process and orthographic autonomy hypothesis with a view to explain how participants with learning disabilities spell written words. Data were collected through interviews, pupils’ exercise books, and progress records, and a spelling test made by the researcher based on the spelling scope set for class three pupils by the ministry of education in the primary education syllabus. The study relied on random sampling techniques in identifying general and specific participants. Since the study used children in schools as participants, voluntary consent was sought from themselves, their teachers and the school head teachers who were their caretakers in a school setting.

Keywords: dysgraphia, writing, language, performance

Procedia PDF Downloads 144

Authors: N. Khanyile, P. Dlamini, M. Masenya

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Background: Most of the population in Africa is still dependent on indigenous medicinal knowledge for treating and managing ailments. Indigenous traditional knowledge owners/practitioners who own this knowledge are consulted by communities, but their knowledge is not known how they get it. The question of how knowledge is acquired and preserved remains one of the biggest challenges in traditional healing and treatment with herbal medicines. It is regrettable that despite the importance and recognition of indigenous medicinal knowledge globally, the details of acquirement, storing and transmission, and preservation techniques are not known. Hence this study intends to unveil the process of acquirement and transmission, and preservation techniques of indigenous medical knowledge by its owners. Objectives: This study aims to assess the process of acquiring and preservation of traditional medicinal knowledge by traditional medicinal knowledge owners/practitioners in uMhlathuze Municipality, in the province of KwaZulu-Natal, South Africa. The study was guided by four research objectives which were to: identify the types of traditional medicinal knowledge owners who possess this knowledge, establish the approach used by indigenous medicinal knowledge owners/healers for acquiring medicinal knowledge, identify the process of preservation of medicinal knowledge by indigenous medicinal knowledge owners/healers, and determine the challenges encountered in transferring the knowledge. Method: The study adopted a qualitative research approach, and a snowball sampling technique was used to identify the study population. Data was collected through semi-structured interviews with indigenous medicinal knowledge owners. Results: The findings suggested that uMhlathuze municipality had different types of indigenous medicinal knowledge owners who possess valuable knowledge. These are diviners (Izangoma), faith healers (Abathandazi), and herbalists (Izinyanga). The study demonstrated that indigenous medicinal knowledge is acquired in many different ways, including visions, dreams, and vigorous training. The study also revealed the acquired knowledge is preserved or shared with specially chosen children and trainees. Conclusion: The study concluded that this knowledge is gotten through vigorous training, which requires the learner to be attentive and eager to learn. It was recommended that a study of this nature be conducted but at a broader level to enhance an informed conclusion and recommendations.

Keywords: preserving, indigenous medicinal knowledge, indigenous knowledge, indigenous medicinal knowledge owners/practitioners, acquiring

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Authors: Ali Isa Danlami

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This study examined the coaching leadership behaviours preferred by athletes in individual and team sports in Nigeria that may lead to increased satisfaction and performance. Six leadership behaviours were identified; these are democratic, training and instruction, situational consideration, autocratic, social support and positive feedback. The six leadership behaviours relate to the preference of coaches by athletes that leads to increased performance were the focus of this study. The population of this study is comprised of male and female athletes of states sports councils in Nigeria. An ex-post facto research design was employed for this study. Stratified and purposive sampling techniques were used to select the sampled states according to the six geo-political zones of the country. Two states (North Central (FCT, Nasarawa), North East (Bauchi, Gombe), North West (Kaduna, Sokoto), South East (Anambra, Imo), South west (Ogun, Ondo), South South (Delta, and Rivers) were selected from each stratum. A modified questionnaire was used to collect data for this study, and the data collected were subjected to a reliability test using the Statistical Package for Social Science (SPSS) to analyse the data. A two sample Z-test procedure was used to test the significant differences because of the large number of subjects involved in the different groups. All hypotheses were tested at 0.05 alpha value. The findings of the study concluded that: Athletes in team and individual sports generally preferred coaches who were more disposed towards training and instructions, social support, positive feedback, situational consideration and democratic behaviours. It was also found that athletes in team sports have higher preference for coaches with democratic behaviour. The result revealed that athletes in team and individual sports did not have a preference for coaches disposed towards autocratic behaviour. Based on this, the following recommendations were made: Democratic behaviour by coaches should be encouraged in team and individual sports. Coaches should not be engaged in autocratic behaviours when coaching. These behaviours should be adopted by coaches to increase athletes’ satisfaction and enhancement in performance.

Keywords: leadership behaviour, preference, athletes, individual, team, coaches’

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Authors: Anupuma Raina, Ajay Parkash

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In forensic investigation, DNA analysis helps in the identification of a particular individual under investigation. A set of Short Tandem Repeats loci are widely used for individualization at a molecular level in forensic testing. STRs with tetrameric repeats of DNA are highly polymorphic and widely used for forensic DNA analysis. Identification of an individual became challenging for forensic examiners after Hematopoietic Stem Cell Transplantation. HSCT is a well-accepted and life-saving treatment to treat malignant and nonmalignant diseases. It involves the administration of healthy donor stem cells to replace the patient’s own unhealthy stem cells. A successful HSCT results in complete donor-derived cells in a patient’s hematopoiesis and hence have the capability to change the genetic makeup of the patient. Although an individual who has undergone HSCT and then committed a crime is a very rare situation, but not impossible. Keeping such a situation in mind, various biological samples like blood, buccal swab, and hair follicle were collected and studied after a certain interval of time after HSCT. Blood was collected from both the patient and the donor before the transplant. The DNA profile of both was analyzed using a short tandem repeat kit for autosomal chromosomes. Among all exhibits studied, only hair follicles were found to be the most suitable biological exhibit, as no donor DNA profile was observed for up to 90 days of study.

Keywords: chimerism, HSCT, STRs analysis, forensic identification

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Authors: Andriana E. Tran, Anna Chur-Hansen

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Sexual health is an important aspect of overall wellbeing. This study aimed to explore the sexual health experiences of men aged 50 years and over from the perspective of health care professional participants who were specializing in sexual health care and who consulted with older men. A total of ten interviews were conducted. Eleven themes were identified regarding men’s experiences with sexual health care as reported by participants. 1) Biologically focused: older male clients focus largely on the biological aspect of their sexual health without consideration of other factors which might affect their functioning. 2) Psychological concerns: there is an interaction between mental and sexual health but older male clients do not necessarily see this. 3) Medicalization of sexual functioning: advances in medicine that aid with erectile difficulties which consequently mean that older men tend to favor a medical solution to their sexual concerns. 4) Masculine identity: sexual health concerns are linked to older male clients’ sense of masculinity. 5) Penile functionality: most concerns that older male clients have center on their penile functionality. 6) Relationships: many male clients seek sexual help as they believe it improves relationships. Conversely, having supportive partners may mean older male clients focus less on the physicality of sex. 7) Grief and loss: men experience grief and loss – the loss of their sexual functioning, grief from loss of a long-term partner, and loss of intimacy and privacy when moving from independent living to residential care. 8) Social stigma: older male clients experience stigma around aging sexuality and sex in general. 9) Help-seeking behavior: older male clients will usually seek mechanistic solution for biological sexual concerns, such as medication used for penile dysfunction. 10) Dismissed by health care professionals: many older male clients seek specialist sexual health care without the knowledge of their doctors as they feel dismissed due to lack of expertise, lack of time, and the doctor’s personal attitudes and characteristics. Finally, 11) Lack of resources: there is a distinct lack of resources and training to understand sexuality for healthy older men. These findings may inform future research, professional training, public health campaigns and policies for sexual health in older men.

Keywords: ageing, biopsychosocial model, men's health, sexual health

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Authors: Maricarmen Herrera, Pierre Chymkowitch, Joe Robertson, Jens Eriksson, Jorrit Enserink

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tRNA genes are transcribed by RNA polymerase III. During recent years, it has become clear that tDNA transcription fluctuates during the cell cycle. However, the mechanism by which the cell cycle controls the amplitude of tDNA transcription remains unknown. We found that the cyclin Clb5 recruits the cyclin dependent kinase Cdk1 to tRNA genes to sharply increase tRNA synthesis during a brief interval in the cell cycle. We show that Cdk1 promotes the interaction of TFIIIB with TFIIIC, that it stimulates the recruitment of TFIIIC to tRNA genes, that it prevents the formation of an overly stable TFIIIB-tDNA complex and that it augments the dynamics of RNA polymerase III. Furthermore, we identify Bdp1 as a novel Cdk1 substrate, and phosphorylation of Bdp1 is required for the cell cycle-dependent increase in tDNA transcription. In addition, we show that phosphorylation of the Cdk1 substrate Nup60 mediates formation of a Nup60-Nup2 complex at tRNA genes, which is also required for cell cycle-dependent tDNA transcription. Together, our findings indicate that Cdk1 activity gates tRNA synthesis by regulating the dynamics of the TFIIIB-TFIIIC-RNAPIII complex, and that it may promote the formation of a nuclear pore microenvironment conducive to efficient tDNA transcription.

Keywords: Cdk1, cell cycle, RNAPIII machinery, tRNA

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Authors: Katerine Moraes dos Satons, Gisele Massante Peixoto Tracera, Regina Célia Gollner Zeitoune

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To analyze the psychosocial risks related to the organization of nursing work in outpatient clinics of university hospitals. Cross-sectional epidemiological study developed in 11 outpatient units linked to the three public universities of the city of Rio de Janeiro, Brazil. Participants were 388 nursing professionals who worked in patient care at the time of the research. Data were collected from July to December 2018, using a self-applicable instrument. A questionnaire was used for sociodemographic, occupational and health characterization, and the Work Organization Scale. The bivariate analyses were performed using the odds ratio (OR), with a confidence interval of 95%, significance level of 5%. The organization of nursing work received an assessment of medium psychosocial risk by the professionals participating in the research, demanding interventions in the short and medium term. There was no association between sociodemographic, occupational and health characteristics and the organization of outpatient work. Interventional measures should be performed in the psychosocial risk factors presented in this research, with a view to improving the work environment, so that the importance of maintaining satisfactory material conditions is considered, as well as the adequate quantity of human resources. In addition, it aims to expand the spaces of nursing participation in decision- making, strengthening its autonomy as a profession.

Keywords: occupational risks, nursing, nursing team, worker’s health, psychosocial risks

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Authors: Shivalal Sharma, Sanjib K. Sharma, Madhab Lamsal

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Background: The aim of this study was to evaluate the clinical and laboratory changes three months after full-mouth scaling and root planing (SRP) in periodontitis patients with type 2 diabetes mellitus (DM). Methods: Forty-seven type 2 DM subjects with moderate to severe periodontitis were randomly divided into two groups. Treatment group (TG), 25 subjects, received full-mouth scaling and root planning; control group (CG), 22 subjects, received no treatment. At baseline and at the end of three months, glycated hemoglobin (HbA1c) values, fasting glucose, and clinical parameters like plaque index (PI), gingival index (GI), probing pocket depth (PPD), and clinical attachment level (CAL) were recorded in all the patients. Following SRP, the patients were enrolled in a monthly interval maintenance program for 3 months. Results: A statistically significant effect could be demonstrated for PI, GI, PPD, and CAL for the treatment group. HbA1c levels in the treatment group decreased significantly whereas the control group showed a slight but insignificant increase for these parameters. Conclusions: The results of this study showed that non-surgical periodontal treatment (SRP) is associated with improved glycemic control in type 2 DM patients and could be undertaken along with the standard measures for the diabetic patient care.

Keywords: periodontitis, type 2 diabetes mellitus, non-surgical periodontal therapy, SRP

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Authors: Teresita Lopez Joy, Jose A. Acevedo Suarez, Martha I. Gomez Acosta, Ana Julia Acevedo Urquiaga

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Current trends in business competitiveness indicate the need to manage businesses as supply chains and not in isolation. The use of strategies aimed at maximum satisfaction of customers in a network and based on inter-company cooperation; contribute to obtaining successful joint results. In the Cuban economic context, the development of productive linkages to achieve integrated management of supply chains is considering a key aspect. In order to achieve this jump, it is necessary to develop acting capabilities in the entities that make up the chains through a systematic procedure that allows arriving at a management model in consonance with the environment. The objective of the research focuses on: designing a model and procedure for the development of integrated management of supply chains in economic entities. The results obtained are: the Model and the Procedure for the Development of the Supply Chains Integrated Management (MP-SCIM). The Model is based on the development of logistics in the network actors, the joint work between companies, collaborative planning and the monitoring of a main indicator according to the end customers. The application Procedure starts from the well-founded need for development in a supply chain and focuses on training entrepreneurs as doers. The characterization and diagnosis is done to later define the design of the network and the relationships between the companies. It takes into account the feedback as a method of updating the conditions and way to focus the objectives according to the final customers. The MP-SCIM is the result of systematic work with a supply chain approach in companies that have consolidated as coordinators of their network. The cases of the edible oil chain and explosives for construction sector reflect results of more remarkable advances since they have applied this approach for more than 5 years and maintain it as a general strategy of successful development. The edible oil trading company experienced a jump in sales. In 2006, the company started the analysis in order to define the supply chain, apply diagnosis techniques, define problems and implement solutions. The involvement of the management and the progressive formation of performance capacities in the personnel allowed the application of tools according to the context. The company that coordinates the explosives chain for construction sector shows adequate training with independence and opportunity in the face of different situations and variations of their business environment. The appropriation of tools and techniques for the analysis and implementation of proposals is a characteristic feature of this case. The coordinating entity applies integrated supply chain management to its decisions based on the timely training of the necessary action capabilities for each situation. Other cases of study and application that validate these tools are also detailed in this paper, and they highlight the results of generalization in the quantitative and qualitative improvement according to the final clients. These cases are: teaching literature in universities, agricultural products of local scope and medicine supply chains.

Keywords: integrated management, logistic system, supply chain management, tactical-operative planning

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Authors: Brenagh E. Schlingermann, Clare Lodge, Paula Rankin

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Background: Gaelic football, hurling and camogie are highly popular field games in Ireland. Research into the epidemiology of injury in Gaelic games revealed that approximately three quarters of the injuries in the games occur in the lower extremity. These injuries can have player, team and institutional impacts due to multiple factors including financial burden and time loss from competition. Research has shown it is possible to record injury data consistently with the GAA through a closed online recording system known as the GAA injury surveillance database. It has been established that determining the incidence of injury is the first step of injury prevention. The goals of this study were to create a dynamic GAA15 injury prevention programme which addressed five key components/goals; avoid positions associated with a high risk of injury, enhance flexibility, enhance strength, optimize plyometrics and address sports specific agilities. These key components are internationally recognized through the Prevent Injury, Enhance performance (PEP) programme which has proven reductions in ACL injuries by 74%. In national Gaelic games the programme is known as the GAA15 which has been devised from the principles of the PEP. No such injury prevention strategies have been published on this cohort in Gaelic games to date. This study will investigate the effects of the GAA15 on injury incidence and neuromuscular function in Gaelic games. Methods: A total of 154 players (mean age 20.32 ± 2.84) were recruited from the GAA teams within the Institute of Technology Carlow (ITC). Preseason and post season testing involved two objective screening tests; Y balance test and Three Hop Test. Practical workshops, with ongoing liaison, were provided to the coaches on the implementation of the GAA15. The programme was performed before every training session and game and the existing GAA injury surveillance database was accessed to monitor player’s injuries by the college sports rehabilitation athletic therapist. Retrospective analysis of the ITC clinic records were performed in conjunction with the database analysis as a means of tracking injuries that may have been missed. The effects of the programme were analysed by comparing the intervention groups Y balance and three hop test scores to an age/gender matched control group. Results: Year 1 results revealed significant increases in neuromuscular function as a result of the GAA15. Y Balance test scores for the intervention group increased in both the posterolateral (p=.005 and p=.001) and posteromedial reach directions (p= .001 and p=.001). A decrease in performance was determined for the three hop test (p=.039). Overall twenty-five injuries were reported during the season resulting in an injury rate of 3.00 injuries/1000hrs of participation; 1.25 injuries/1000hrs training and 4.25 injuries/1000hrs match play. Non-contact injuries accounted for 40% of the injuries sustained. Year 2 results are pending and expected April 2016. Conclusion: It is envisaged that implementation of the GAA15 will continue to reduce the risk of injury and improve neuromuscular function in collegiate Gaelic games athletes.

Keywords: GAA15, Gaelic games, injury prevention, neuromuscular training

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Authors: Thapa M., J.P. Dutta, K.R. Pandey, R.R. Kattel

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Nepal is extremely vulnerable to the impact of climate change. To mitigate the climate change effects on agricultural production and productivity a range of adaptive strategies needs to be considered. The study was conducted to assess organic paddy production as a coping strategy to the adverse impact of climate change in Phulbari, VDC of Chitwan district. Altogether, 120 respondents (60 adopters of organic farming and 60 from non adopter) were selected using snowball technique of sampling. Pre- tested interview schedule, direct observation, focus group discussion, key informant interview as well as secondary data were used to collect the required information. Factors determining the adoption of organic farming were found to be age, year of schooling, training, frequency of extension contact, perception about climate change, economically active members and poor. A unit increase in these factors except poor would increase the probability of adoption by 4.1%, 7.5%, 7.8%, 43.1%, 41.8% and 7% respectively. However, for poor, it would decrease the probability of adoption of organic farming by 5.1%. Average organic matter content in the adopters' field was higher (2.7%) than the non-adopters' field (2.5%). The regression result showed that type of farmer, price and area under rice cultivation had positive and significant relationship with income; however dependency ratio had negative relationship. As the year of adoption of organic farming increases, the production of rice decline in the first two years then after goes on increasing but the cost of production goes on decreasing with the year of adoption. The respondents adapted to the changing climate through diversification of crops, use of resistance varieties and following good cropping pattern. Gradually growing consumers' awareness about health, preference towards quality food products are the strong points behind organic farming, whereas lacks of bio-fertilizers, lack of effective extension services, no price differentiation between organic and inorganic products were the weak points. There is need for more training and education to change the attitude of farmers and enhance their confidence about the role of organic farming to cope with climate change impact.

Keywords: Organic farming, climate change, sustainable development

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Authors: Mohammed Ketel

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This paper discusses the security issues related to Bring Your Own Devices (BYOD) programs, an increasingly popular choice for small and big businesses alike, and explores the benefits, risks, the available controls and solutions to mitigate the inherent security concerns with mobile devices, in general, and BYOD programs specifically. The paper also discusses the approaches that organizations can apply to mitigate the risks, which may include policies, diverse technologies, education, and training.

Keywords: BYOD, security, policies, standards, controls, education

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Authors: Omar Nasani, Chaza Kouchaji, Muznah Alkhani, Maisaa Abd-alkareem

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Objective: To evaluate the influence of sweetening agents used in pediatric medications on the growth of Streptococcus mutans colonies and its effect on the cariogenic activity in the oral cavity. No previous studies are registered yet in Syrian children. Methods: Specimens were isolated from the oral cavity of pediatric patients, then in-vitro study is applied on locally manufactured liquid pediatric antibiotic drugs, containing natural or synthetic sweeteners. The selected antibiotics are Ampicillin (sucrose), Amoxicillin (sucrose), Amoxicillin + Flucloxacillin (sorbitol), Amoxicillin+Clavulanic acid (Sorbitol or sucrose). These antibiotics have a known inhibitory effect on gram positive aerobic/anaerobic bacteria especially Streptococcus mutans strains in children’s oral biofilm. Five colonies are studied with each antibiotic. Saturated antibiotics were spread on a 6mm diameter filter disc. Incubated culture media were compared with each other and with the control antibiotic discs. Results were evaluated by measuring the diameter of the inhibition zones. The control group of antibiotic discs was resourced from Abtek Biologicals Ltd. Results: The diameter of inhibition zones around discs of antibiotics sweetened with sorbitol was larger than those sweetened with sucrose. The effect was most important when comparing Amoxicillin + Clavulanic Acid (sucrose 25mm; versus sorbitol 27mm). The highest inhibitory effect was observed with the usage of Amoxicillin + Flucloxacillin sweetened with sorbitol (38mm). Whereas the lowest inhibitory effect was observed with Amoxicillin and Ampicillin sweetened with sucrose (22mm and 21mm). Conclusion: The results of this study indicate that although all selected antibiotic produced an inhibitory effect on S. mutans, sucrose weakened the inhibitory action of the antibiotic to varying degrees, meanwhile antibiotic formulations containing sorbitol simulated the effects of the control antibiotic. This study calls attention to effects of sweeteners included in pediatric drugs on the oral hygiene and tooth decay.

Keywords: pediatric, dentistry, antibiotics, streptococcus mutans, biofilm, sucrose, sugar free

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Authors: Shreya Poddar

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Legal drafting and revising are recognized as highly demanding tasks for legal professionals. This paper introduces an approach to automate and refine these processes through the use of advanced Artificial Intelligence (AI). The method employs Large Language Models (LLMs), with a specific focus on 'Chain of Thoughts' (CoT) and knowledge injection via prompt engineering. This approach differs from conventional methods that depend on comprehensive training or fine-tuning of models with extensive legal knowledge bases, which are often expensive and time-consuming. The proposed method incorporates knowledge injection directly into prompts, thereby enabling the AI to generate more accurate and contextually appropriate legal texts. This approach substantially decreases the necessity for thorough model training while preserving high accuracy and relevance in drafting. Additionally, the concept of guardrails is introduced. These are predefined parameters or rules established within the AI system to ensure that the generated content adheres to legal standards and ethical guidelines. The practical implications of this method for legal work are considerable. It has the potential to markedly lessen the time lawyers allocate to document drafting and revision, freeing them to concentrate on more intricate and strategic facets of legal work. Furthermore, this method makes high-quality legal drafting more accessible, possibly reducing costs and expanding the availability of legal services. This paper will elucidate the methodology, providing specific examples and case studies to demonstrate the effectiveness of 'Chain of Thoughts' and knowledge injection in legal drafting. The potential challenges and limitations of this approach will also be discussed, along with future prospects and enhancements that could further advance legal work. The impact of this research on the legal industry is substantial. The adoption of AI-driven methods by legal professionals can lead to enhanced efficiency, precision, and consistency in legal drafting, thereby altering the landscape of legal work. This research adds to the expanding field of AI in law, introducing a method that could significantly alter the nature of legal drafting and practice.

Keywords: AI-driven legal drafting, legal automation, futureoflegalwork, largelanguagemodels

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Authors: Jae Ni Jang, Young Uk Kim

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Background: Chat Generative Pre-training Transformer-3 (ChatGPT; San Francisco, California, Open Artificial Intelligence) is an artificial intelligence chatbot based on a large language model designed to generate human-like text. As the usage of ChatGPT is increasing among less knowledgeable patients, medical students, and anesthesia and pain medicine residents or trainees, we aimed to evaluate the accuracy of ChatGPT-3 responses to questions about the American Society of Anesthesiologists (ASA) classification based on patients’ underlying diseases and assess the quality of the generated responses. Methods: A total of 47 questions were submitted to ChatGPT using textual prompts. The questions were designed for ChatGPT-3 to provide answers regarding ASA classification in response to common underlying diseases frequently observed in adult patients. In addition, we created 18 questions regarding the ASA classification for pediatric patients and pregnant women. The accuracy of ChatGPT’s responses was evaluated by cross-referencing with Miller’s Anesthesia, Morgan & Mikhail’s Clinical Anesthesiology, and the American Society of Anesthesiologists’ ASA Physical Status Classification System (2020). Results: Out of the 47 questions pertaining to adults, ChatGPT -3 provided correct answers for only 23, resulting in an accuracy rate of 48.9%. Furthermore, the responses provided by ChatGPT-3 regarding children and pregnant women were mostly inaccurate, as indicated by a 28% accuracy rate (5 out of 18). Conclusions: ChatGPT provided correct responses to questions relevant to the daily clinical routine of anesthesiologists in approximately half of the cases, while the remaining responses contained errors. Therefore, caution is advised when using ChatGPT to retrieve anesthesia-related information. Although ChatGPT may not yet be suitable for clinical settings, we anticipate significant improvements in ChatGPT and other large language models in the near future. Regular assessments of ChatGPT's ASA classification accuracy are essential due to the evolving nature of ChatGPT as an artificial intelligence entity. This is especially important because ChatGPT has a clinically unacceptable rate of error and hallucination, particularly in pediatric patients and pregnant women. The methodology established in this study may be used to continue evaluating ChatGPT.

Keywords: American Society of Anesthesiologists, artificial intelligence, Chat Generative Pre-training Transformer-3, ChatGPT

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Authors: Jonas Sanon

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The valorization of research is becoming a transversal instrument linking different sectors (academic, public and industrial). The practice of valorization seems to impact innovation techniques within companies where, there is often the implementation of industrial conventions of training through research (CIFRE), continuous training programs for employees, collaborations and partnerships around joint research and R&D laboratories focused on the needs of companies to improve or develop more efficient innovations. Furthermore, many public initiatives to support innovation and technology transfer have been developed at the international, European and national levels, with significant budget allocations. Thus, in the context of this work, we tried to analyze the way in which research transfer structures are evaluated within the Saclay ecosystem. In fact, the University-Paris-Saclay is one of the best French universities; it is made up of 10 university components, more than 275 laboratories and is in partnership with the largest French research centers This work mainly focused on how evaluations affected research transfer structures, how evaluations were conducted, and what the managers of research transfer structures thought about assessments. Thus, with the aid of the conducted interviews, it appears that the evaluations do not have a significant impact on the qualitative aspect of research and innovation, but is rather present a directive aspect to allow the structures to benefit or not from the financial resources to develop certain research work, sometimes directed and influenced by the market, some researchers might try to accentuate their research and experimentation work on themes that are not necessarily their areas of interest, but just to comply with the calls for proposed thematic projects. The field studies also outline the primary indicators used to assess the effectiveness of valorization structures as "the number of start-ups generated, the license agreements signed, the structure's patent portfolio, and the innovations of items developed from public research.". Finally, after mapping the actors, it became clear that the ecosystem of the University of Paris-Saclay benefits from a richness allowing it to better value its research in relation to the three categories of actors it has (internal, external and transversal), united and linked by a relationship of proximity of sharing and endowed with a real opportunity to innovate openly.

Keywords: research valorization, technology transfer, innovation, evaluation, impacts and performances, innovation policy

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Rodrigo Arnaldo Scarpel

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Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.

Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation

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