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Drop-Out in Higher Education: The Problem must be Concern and Solve / การออกกลางคันในระดับอุดมศึกษา: ปัญหาที่ต้องเร่งให้ความสนใจและแก้ไข
No full textการเข้าศึกษาต่อระดับอุดมศึกษาในประเทศไทย มีวิธีการคัดเลือกทั้งแบบระบบรับตรงและระบบส่วนกลาง ซึ่งกว่าที่จะเข้าศึกษาต่อได้นั้น ต้องสูญเสียทั้งเวลาและทรัพย์สินเป็นจำนวนมาก แต่เมื่อนิสิตได้เข้ามาศึกษาแล้วยังมีบางส่วนต้องออกจากระบบการศึกษาไป ซึ่งเราเรียกว่า “การออกกลางคัน” นับเป็นการสูญเปล่าทางการศึกษา โดยการออกกลางคันนี้เป็นปัญหาหนึ่งของการศึกษาในระดับอุดมศึกษา มีสาเหตุมาจาก 2 ปัจจัยหลัก ได้แก่ 1) คุณลักษณะส่วนบุคคลของนิสิต ได้แก่ ความรับผิดชอบ สุขภาพ ความสัมพันธ์ในครอบครัวของนิสิต สถานะทางเศรษฐกิจ ผลการเรียนเดิม และการตัดสินใจเลือกคณะที่ศึกษาต่อ 2) คุณลักษณะภายนอกที่เกี่ยวข้องกับนิสิต ได้แก่ การจัดการศึกษาของสถาบันการศึกษา อาจารย์ผู้สอน อาจารย์แนะแนว และอาจารย์ประจำชั้น คำสำคัญ: การออกกลางคัน การสูญเปล่าทางการศึกษา อุดมศึกษา Method to entrance in higher education have Central university admissions system and Direct system. It is difficult to entrance But someone get out before success, “Drop out”. There have two main causes are 1) Personalities of student are responsibility, health, relationship in family, economic, achievement and decision to study. 2) Environment of student are education administration teacher-counselor and class teacher. Keywords: Drop-Out, Education Wastage, Higher Educatio
Effect of Learning Outcome Using Conceptual Change Teaching Strategy in Radioactivity and Nuclear Energy Topics for MatayomSuks IV Students / ผลการจัดการเรียนรู้โดยใช้กลวิธีสอนเพื่อเปลี่ยนมโนมติ เรื่อง กัมมันตภาพรังสีและพลังงานนิวเคลียร์ของนักเรียนชั้นมัธยมศึกษาปีที่ 4
No full text เนื่องจากเนื้อหาเรื่องกัมมันตภาพรังสีและพลังงานนิวเคลียร์เป็นนามธรรมและเป็นเรื่องยาก นักเรียนส่วนมากมีมโนมติคลาดเคลื่อน งานวิจัยครั้งนี้จึงมีวัตถุประสงค์เพื่อศึกษาการเปลี่ยนความเข้าใจมโนมติ เรื่อง กัมมันตภาพรังสีและพลังงานนิวเคลียร์ ของนักเรียนระดับชั้นมัธยมศึกษาปีที่ 4 โดยใช้กลวิธีสอนเพื่อเปลี่ยนมโนมติ ซึ่งประกอบด้วย กิจกรรมการเรียนรู้ 3 กิจกรรม ได้แก่ การเปรียบเทียบ การใช้เอกสารเปลี่ยนมโนมติ และบทบาทสมมติ กลุ่มตัวอย่างเป็นนักเรียนระดับชั้นมัธยมศึกษาปีที่ 4 ของโรงเรียนขนาดใหญ่แห่งหนึ่งในจังหวัดพิษณุโลก จำนวน 25 คน โดยการคัดเลือกแบบเจาะจง เครื่องมือที่ใช้ในการวิจัยครั้งนี้ ประกอบด้วย แบบสัมภาษณ์มโนมติ แผนการจัดการเรียนรู้เพื่อเปลี่ยนมโนมติ และแบบบันทึกการเรียนรู้ วิเคราะห์ข้อมูลโดยหาค่าความถี่และค่าร้อยละของนักเรียนที่มีความเข้าใจมโนมติถูกต้อง ความเข้าใจมโนมติถูกต้องบางส่วน ความเข้าใจมโนมติคลาดเคลื่อนและความไม่เข้าใจ ผลการวิจัย พบว่า การจัดการเรียนรู้โดยใช้กลวิธีสอนเพื่อเปลี่ยนมโนมติ สามารถช่วยให้นักเรียนมีการเปลี่ยนความเข้าใจมโนมติ เรื่อง กัมมันตภาพรังสีและพลังงานนิวเคลียร์ โดยนักเรียนเปลี่ยนมโนมติเป็นความเข้าใจถูกต้องและความเข้าใจมโนมติถูกต้องบางส่วนเพิ่มขึ้น ขณะเดียวกันความเข้าใจมโนมติคลาดเคลื่อนและความไม่เข้าใจมโนมติลดลง ผลการวิจัยที่ได้เป็นการเสนอแนวทางให้ครูนำไปใช้ในการจัดการเรียนการสอน เพื่อพัฒนาความเข้าใจมโนมติวิทยาศาสตร์ คำสำคัญ: ความเข้าใจมโนมติ การเปลี่ยนมโนมติ กัมมันตภาพรังสี พลังงานนิวเคลียร์ กลวิธีสอน The content of radioactivity and nuclear energy topics as an abstract and difficult, most student have misunderstanding. This research aimed to explore conceptual change in radioactivity and nuclear energy topics for Matayomsuksa IV Student by using conceptual change teaching strategies, which were analogy, refutation text and role-playing. The participants were 25 Matayomsuksa IV students in a secondary school in Phitsanulok province was situated by purposive sampling. The tools employed in this research were interviews, lesson plan for conceptual change and journals. The frequency and the percentage of student sound understandings, student partial understandings, student misunderstandings and student no understandings were used to analyze the student conceptions. The result indicated that learning process by using conceptual change teaching strategies could develop the students’ scientific conceptions about radioactivity and nuclear energy. Although some students did not change in some conceptions. They improved their reasoning and explaining skills. This research results can be a guideline teachers in using an instructional management to encourage student to have scientific understanding. Keywords: Conceptual Understanding, Conceptual Change, Radioactivity, Nuclear Energy, Teaching Strategie
Electrical stimulation enhances epidermal proliferation in human cutaneous wounds by modulating p53-SIVA1 interaction
No full textCutaneous wounds establish endogenous "wound current" upon injury until re-epithelialization is complete. Keratinocyte proliferation, regulated partly by p53, is required for epidermal closure. SIVA1 promotes human double minute 2 homolog (HDM2)-mediated p53 regulation. However, the role of SIVA1 in wound healing is obscure. Here, we report that electrical stimulation (ES) accelerates wound healing by upregulating SIVA1 and its subsequent ability to modulate p53 activities. Cultured donut-shaped human skin explants, subjected to ES, exhibited better epidermal stratification, increased proliferation, and upregulation of gene and protein expression of HDM2/SIVA1, compared with non-ES-treated explants. ES significantly increased in vitro keratinocyte proliferation and phospho-p53-SIVA1 interaction; however, this showed stable expression of phospho-p53, which increased significantly in the absence of SIVA1. Here, HDM2 alone was unable to downregulate nuclear-accumulated phospho-p53, which was evident from decreased proliferation and increased sub-G1 population seen by flow cytometry. Further examination of the epidermis of human cutaneous wounds showed higher p53-SIVA1 coexpression and proliferation 7 days after injury in ES-treated wounds compared with control wounds. In summary, ES-inducible SIVA1 modulates p53 activities in proliferating keratinocytes, and exogenous ES affects p53/HDM2/SIVA1 axis leading to increased proliferation during re-epithelialization. This highlights ES as a potential strategy for enhancing cutaneous repair
Assessing the effects of load models on MV network losses
No full textNetwork losses are often a key metric in evaluating the performance of planning and/or operational strategies. However, their assessment is traditionally carried out assuming a constant power load model that does not reflect the actual voltage-demand dependency, thus leading to inaccurate results. This work quantifies, in a real UK medium voltage (MV) network, the impact of three classic load models (constant power, current and impedance) on the quantification of energy and power network losses. A time-varying ZIP model designed for the UK residential demand is used as benchmark. Results indicate that the constant power load model, although underestimates the network losses throughout the year, outperforms the other models during summer (maximum error of 3% on power and 1.5% in energy). However, during winter the constant current model showed the best performance. The constant impedance model led to the highest errors and, consequently, should be in general avoided
Anastrozole versus tamoxifen for the prevention of locoregional and contralateral breast cancer in postmenopausal women with locally excised ductal carcinoma in situ (IBIS-II DCIS): a double-blind, randomised controlled trial
No full textBackground Third-generation aromatase inhibitors are more eff ective than tamoxifen for preventing recurrence in postmenopausal women with hormone-receptor-positive invasive breast cancer. However, it is not known whether anastrozole is more eff ective than tamoxifen for women with hormone-receptor-positive ductal carcinoma in situ (DCIS). Here, we compare the effi cacy of anastrozole with that of tamoxifen in postmenopausal women with hormone-receptor-positive DCIS. Methods In a double-blind, multicentre, randomised placebo-controlled trial, we recruited women who had been diagnosed with locally excised, hormone-receptor-positive DCIS. Eligible women were randomly assigned in a 1:1 ratio by central computer allocation to receive 1 mg oral anastrozole or 20 mg oral tamoxifen every day for 5 years. Randomisation was stratifi ed by major centre or hub and was done in blocks (six, eight, or ten). All trial personnel, participants, and clinicians were masked to treatment allocation and only the trial statistician had access to treatment allocation. The primary endpoint was all recurrence, including recurrent DCIS and new contralateral tumours. All analyses were done on a modifi ed intention-to-treat basis (in all women who were randomised and did not revoke consent for their data to be included) and proportional hazard models were used to compute hazard ratios and corresponding confi dence intervals. This trial is registered at the ISRCTN registry, number ISRCTN37546358. Results Between March 3, 2003, and Feb 8, 2012, we enrolled 2980 postmenopausal women from 236 centres in 14 countries and randomly assigned them to receive anastrozole (1449 analysed) or tamoxifen (1489 analysed). Median follow-up was 7·2 years (IQR 5·6–8·9), and 144 breast cancer recurrences were recorded. We noted no statistically signifi cant diff erence in overall recurrence (67 recurrences for anastrozole vs 77 for tamoxifen; HR 0·89 [95% CI 0·64–1·23]). The non-inferiority of anastrozole was established (upper 95% C
Artificial Intelligence systems as prognostic and predictive tools in ovarian cancer
No full textBACKGROUND: The ability to provide accurate prognostic and predictive information to patients is becoming increasingly important as clinicians enter an era of personalized medicine. For a disease as heterogeneous as epithelial ovarian cancer, conventional algorithms become too complex for routine clinical use. This study therefore investigated the potential for an artificial intelligence model to provide this information and compared it with conventional statistical approaches. METHODS: The authors created a database comprising 668 cases of epithelial ovarian cancer during a 10-year period and collected data routinely available in a clinical environment. They also collected survival data for all the patients, then constructed an artificial intelligence model capable of comparing a variety of algorithms and classifiers alongside conventional statistical approaches such as logistic regression. RESULTS: The model was used to predict overall survival and demonstrated that an artificial neural network (ANN) algorithm was capable of predicting survival with high accuracy (93 %) and an area under the curve (AUC) of 0.74 and that this outperformed logistic regression. The model also was used to predict the outcome of surgery and again showed that ANN could predict outcome (complete/optimal cytoreduction vs. suboptimal cytoreduction) with 77 % accuracy and an AUC of 0.73. CONCLUSIONS: These data are encouraging and demonstrate that artificial intelligence systems may have a role in providing prognostic and predictive data for patients. The performance of these systems likely will improve with increasing data set size, and this needs further investigation
Ten years of QconCATs: Application of multiplexed quantification to small medically-relevant proteomes
No full textIn this report, we briefly review the application of Beynon and Gaskell’s QconCAT methodology to the quantification of a variety of proteomes. We then describe the development of two QconCATs, intended for the analysis of small proteomes relevant to human medicine: the bacterial ribosome (30SCAT) and the human drug-metabolizing enzymes (cytochrome P450 and uridine 5′-diphospho-glucuronosyltransferase enzymes: MetCAT). The design of both QconCATs was supported by experimental identification of proteotypic peptides, leading to redundancy of information during quantification, and providing good evidence for complete digestion of both analyte and QconCAT. Both QconCATs are designed to be used with sequential LysC and trypsin digestion, and in the case of the 30SCAT, two LC MS/MS measurements are made, one following each digestion step. The MetCAT initially failed to express; successful expression was achieved in two ways: by a reshuffle of the order of the peptides, and by fusion of the original construct with the 30SCAT gene. Both QconCATs have been used to quantify samples of importance in human medicine
Deliverable 2.2 "Benefits of controlling EVs and PV"
No full textThis report presents a quantitative assessment of the benefits of adopting control of EVs and PV systems considering different control strategies, penetration of low carbon technologies, and penetrations per feeder, and types of LV networks
Graphene/Elastomer Nanocomposites
No full textIn the decade since the first isolation and identification of graphene, the scientific community is still finding ways to utilize its unique properties. The present review deals with the preparation and physicochemical characterization of graphene-based elastomeric nanocomposites. The processing and characterization of graphene and graphene oxide are described in detail, since the presence of such fillers in an elastomeric matrix affects dramatically the properties of the nanocomposite samples. Several preparation routes for the efficient dispersion of graphene in elastomers are then discussed, while aspects such as the interfacial bonding between the filler and the matrix or interactions between the fillers have been thoroughly analysed. Different types of graphene/elastomer nanocomposites are described in terms of their manufacture and properties and it has been shown that depending on the type of graphene employed and the preparation methods, the mechanical, thermal, electrical and barrier properties of the elastomeric matrix can be enhanced due to the presence of graphene, even at relatively-low filler loadings. In most cases, the formation of a filler network can play a major role in the improvement of the overall performance of the material
Methods and software tools for design evaluation in population pharmacokinetics-pharmacodynamics studies.
No full textPopulation pharmacokinetic (PK)-pharmacodynamic (PKPD) models are increasingly used in drug development and in academic research; hence, designing efficient studies is an important task. Following the first theoretical work on optimal design for nonlinear mixed-effects models, this research theme has grown rapidly. There are now several different software tools that implement an evaluation of the Fisher information matrix for population PKPD. We compared and evaluated the following five software tools: PFIM, PkStaMp, PopDes, PopED and POPT. The comparisons were performed using two models, a simple-one compartment warfarin PK model and a more complex PKPD model for pegylated interferon, with data on both concentration and response of viral load of hepatitis C virus. The results of the software were compared in terms of the standard error (SE) values of the parameters predicted from the software and the empirical SE values obtained via replicated clinical trial simulation and estimation. For the warfarin PK model and the pegylated interferon PKPD model, all software gave similar results. Interestingly, it was seen, for all software, that the simpler approximation to the Fisher information matrix, using the block diagonal matrix, provided predicted SE values that were closer to the empirical SE values than when the more complicated approximation was used (the full matrix). For most PKPD models, using any of the available software tools will provide meaningful results, avoiding cumbersome simulation and allowing design optimization