bluuebunny/crossref_metadata_2025 huggingface dataset:
Respon Tanaman Cabai Rawit (Capsicum frutescens L.) Varietas Pelita F1 terhadap Penggenangan
Authors: Raras RR Pascalina , Saptiningsih Endang , Haryanti Sri
Published: October 2021

Cabai rawit (Capsicum frutescens L.) merupakan salah satu tanaman yang memiliki nilai ekonomi tinggi dan daya adaptasi yang cukup luas. Curah hujan tinggi di Indonesia mengakibatkan lahan tergenang sehingga mengancam produktivitas tanaman, salah satunya cabai rawit. Tujuan penelitian ini untuk mengetahui respon dan toleransi tanaman cabai rawit (C. frutescens L.) varietas Pelita F1 terhadap penggenangan. Perlakuan terdiri dari kontrol (kapasitas lapang) dan perlakuan penggenangan selama 24 jam. Perlakuan menggunakan 2 atau 3 ulangan. Desain penelitian menggunakan RAL dan analisis data menggunakan ANOVA dan uji lanjut LSD taraf signifikan 5%. Hasil penelitian menunjukkan terjadi penurunan persentase layu, kerusakan ujung akar, penurunan kandungan klorofil a, klorofil b, klorofil total dan karotenoid setelah penggenangan. Tanaman terlihat segar, jumlah daun dipertahankan, terjadi pertumbuhan akar, peningkatan kandungan pigmen fotosintesis, tinggi tanaman dan berat kering pada akhir fase pemulihan. Terjadinya pertumbuhan diakhir fase pemulihan menunjukkan cabai varietas Pelita F1 toleran terhadap penggenangan 24 jam. Kemampuan tanaman dalam memperbaiki sistem perakaran, mempertahankan jumlah daun dan meningkatkan kandungan pigmen fotosintesis merupakan faktor penting dalam toleransi tanaman terhadap penggenangan.
Kandungan Klorofil dan Karotenoid Daun Salam (Syzigium polyanthum (Wight) Walp.) pada Umur yang Berbeda
Authors: Khafid Abdul , Nurchayati Yulita , Suedy Sri Widodo Agung
Published: October 2021

Pohon salam (Syzygium polyanthum (Wight) Walp.) merupakan salah satu tumbuhan yang daunnya sering dimanfaatkan oleh masyarakat di berbagai daerah di Indonesia sebagai penyedap rasa dalam masakan dan obat-obatan tradisional. Daun salam umumnya dimanfaatkan dalam kondisi segar. Pemanfaatan daun segar tersebut dilakukan berdasar umur daun, yang berkaitan dengan kandungan bahan aktifnya. Penelitian ini bertujuan untuk mengetahui kandungan pigmen klorofil dan karotenoid daun salam pada umur yang berbeda. Penelitian menggunakan Rancangan Acak Lengkap, sampel daun diambil dari urutan daun yang berbeda berdasarkan letak duduk daun yaitu urut dari daun paling ujung (muda) merupakan daun ke-1, ke-3, ke-5, dan daun ke-7. Ulangan sebanyak 3 kali dari tangkai pohon yang berbeda. Parameter yang diamati adalah kandungan klorofil-a, klorofil-b, klorofil total dan karotenoid yang diukur secara spektrofotometri. Data dianalisis menggunakan ANOVA dilanjutkan dengan DMRT. Hasil penelitian menunjukkan bahwa Kandungan pigmen klorofil dan karotenoid meningkat seiring pertambahan umur daun. Kandungan klorofil-a tertinggi pada daun ke-3, sementara klorofil-b,klorofil total dan karotenoid tertinggi pada daun ke-5.
Kadar Trigliserida Daging Keturunan F1 Betina dari Induk Puyuh Jepang (Coturnix coturnix japonica L.) yang Diberi Suplemen Tepung Kunyit (Curcuma longa L.) dalam Pakan.
Authors: Adjie Danar Janu , Tana Silvana , Saraswati Tyas Rini
Published: October 2021

ABSTRAKPuyuh merupakan salah satu komoditi peternakan yang mempunyai peran dalam pemenuhan kebutuhan akan protein hewani berupa telur dan daging. Penelitian ini bertujuan untuk mengetahui kadar trigliserida daging puyuh pada keturunan F1 betina dari induk puyuh yang diberi suplemen tepung kunyit dalam pakan sebagai upaya menghasilkan anak puyuh kualitas unggul dengan kondisi fisiologis yang baik. Penelitian ini menggunakan metode eksperimental dengan Rancangan Acak Lengkap (RAL). Hewan percobaan yang digunakan adalah 15 ekor puyuh jepang (Coturnix coturnix japonica L.) betina, yang dibagi kedalam 3 kelompok perlakuan dengan 5 kali ulangan, yaitu K0: keturunan F1 betina dari induk yang tidak diberi suplemen tepung kunyit,K1: keturunan F1 betina dari induk puyuh yang diberi suplemen tepung kunyit dengan dosis 54 mg/ekor/hari sebelum masa kelamin dan K2 : keturunan F1 betina dari induk puyuh yang diberi sumplemen tepung kunyit dengan dosis 108 mg/ekor/hari sebelum masa kelamin. Data dianalisis dengan menggunakan analisis of varian (ANOVA). Hasil penelitian menunjukkan bahwa konsumsi pakan harian, konsumsi minum harian dan kadar trigliserida daging pada keturunan F1 betina dari induk yang diberi suplemen tepung kunyit tidak berbeda nyata, sehingga dapat disimpulkan bahwa kondisi fisiologis pada keturunan F1 betina dalam kondisi normal.
Unfolding knowledge co-construction processes through social annotation and online collaborative writing with text mining techniques
Authors: Li Sandy C , Lai Tony K. H.
Published: October 2021

Despite the positive claims on the pedagogical use of social annotation and online collaborative writing tools discussed in the literature, most of the findings are derived from interviews or self-reported survey data. Very few studies probed deep into the learning processes and examined students’ digital traces and the artefacts they co-construct. In this study, we employed semantic network analysis techniques to examine how the use of a social annotation tool (Diigo) coupled with an online collaborative writing (Google Docs) affects students’ learning outcomes. The results indicate that the use of Diigo coupled with Google Docs helps enhance student engagement in the collaborative process and that the concept connectivity and quality of the text co-constructed by each group using Diigo coupled with Google Docs is significantly higher than those using Moodle’s forum. In addition, the level of collaboration within a group correlates positively with the number of vertices with high lexical relevancy identified in the semantic network of the text co-constructed by each group.
Implications for practice and policy:

Undergraduate students can use Diigo coupled with Google Docs to enhance their collaborative work.
Course leaders could use Diigo coupled with Google Docs to support learning activities, such as flipped learning or collaborative inquiry learning, in which students are required to engage in close reading and the co-construction of artefacts.
Course instructors could consider using semantic measures such as the number of clusters and betweenness centrality to assess the quality of students’ co-constructed artefacts.
Design of optical packet switch in presence of dispersion compensation and amplifier noise
Authors: Chandra Sumit , Fatima Shahnaz , Suryavanshi Raghuraj Singh
Published: October 2021

Optical communication gained popularity in past few years. Optical communication has many distinct advantages over copper cable based electronic communication. Optical switches are integral part of optical networks which are used for rerouting of packets and also plays important role in contention resolution of the packets. These switch uses fiber delay lines (FDLs) act as optical memory. In past analysis of the switch is done by considering loss, power and noise and finally bit error rate (BER); however dispersion was neglected which is an important parameter in high speed communication. In this paper, design analysis is done by considering dispersion compensation along with optical amplifier noise.
Comintern Aesthetics in the Andes: The Indigenous Revolutionary
Authors: Einarsdóttir Anna Björk
Published: October 2021

The fight against imperialism and racism was central to the Comintern's political and cultural program of the interwar period. Although the more immediate interests of the Soviet state would come to overshadow such causes, the cultural and political connections forged during this time influenced later forms of organizing. Throughout the interwar period (1918-39), the Soviet Union served as the core location of a newly formed world-system of socialist and communist radicalism. The origin of Latin American Marxism in the work of the Peruvian theorist and political organizer José Carlos Mariátegui, as well as the politically committed literature associated with the interwar communist left in the Andean region of Latin America, shows how literature and theory devoted to the indigenous revolutionary contributed to interwar Marxist debates. The interwar influence of Mariátegui and César Vallejo makes clear the importance of resisting attempts to drive a wedge between the two authors and the broader communist movement at the time.
Dialectical Materialisms, Metabolic Rifts and the Climate Crisis: A Lacanian/Hegelian Perspective
Authors: Heron Kai
Published: October 2021

Metabolic rift theory has been accused of assuming an untenable ontological dualism between nature and society. In response, two of its leading advocates, John Bellamy Foster and Andreas Malm, have tried to argue that the approach is not dualist but rather rigorously realist, nonreductively naturalist, and dialectically materialist. According to Foster and Malm, metabolic rift theory is essential because it enables eco-Marxism to make an analytic distinction between nature and society while nevertheless grasping their complex interrelation. From a Lacanian and Hegelian perspective, Foster and Malm are right to preserve the dialectical distinction between nature and society but their respective accounts of this dialectic are insufficiently materialist. Foster falls into a pre-Marxian contemplative materialism. Malm hesitates between his intended realism and Kantian idealism. For metabolic rift theory to be put on a firmer materialist footing, nature must be thought along Lacanian and Hegelian lines as incomplete, thwarted, or shot through with antagonisms out of which emerge the subject and society. To put this in dialectical terms: ontologically there is only nature, out of which society and the subject emerge as an effect of nature's failure to be fully natural.
Periwinkle Shell as Mixing Ingredient in Concrete: A Review
Authors: RUSLAN HANIS NADIAH , Muthusamy Khairunisa , Syed Mohsin Sharifah Maszura , Kirgiz M. S.
Published: October 2021

Growing population which also pushes for rising demand for seafood results in a generation of seashells which are thrown as environmental pollution waste after the edible meat is consumed. Meanwhile, the utilisation of natural resources as mixing ingredients for the production of concrete materials continues to increase over the year. The use of periwinkle shells as mixing ingredients in concrete materials can lower the dependency on natural aggregate supply. This paper discusses the properties of periwinkle shell and method of treatment prior to their usage as a cement and coarse aggregate as well as the mechanical properties of concrete produced using this seashell waste. Overall, the replacement of periwinkle shell as cement and coarse aggregate must be integrated in a specified percentage to enhance the performance of the concrete. For cement replacement, 5% of replacement gives the highest strength, meanwhile 10% of replacement as coarse aggregate can meet the desired strength. The increase in the use of periwinkle shell quantity as cement or coarse aggregate replacement reduces concrete workaibility. The integration of periwinkle shell influences the compresssive strength of concrete. Accomplishment in replacing periwinkle shell as cement and coarse aggregate would reduce pollutiion due to shell dumping and save natural resources. However, further investigation in terms of durability properties is recommended.
Cockle Shell as Mixing Ingredient in Concrete: A Review
Authors: Mohamad Nabilla , Muthusamy Khairunisa , El Gelany Ismail Mohamed Abdel Kader
Published: October 2021

The demand for the population is boosting the production of edible and non-edible products that produce by-products that result in emissions being thrown as waste. The successful cockle trade also creates vestiges of cockle shell that are thrown away as waste. Despite the effects of climate change, industrial activity including calcareous and granite mining to satisfy the need for cement and concrete production, respectively, cannot be prevented as more structures are developed worldwide. The mechanical properties of concrete containing crushed cockle shell as partial fine aggregate, coarse aggregate and cement replacement were examined and reported in this paper. Cockle shell powder was used as cement replacement up to 75%. To sum up, the use of cockle shell is an appealing option for the construction industry and sustainable green climate.
Settlement Analysis of Treated Soft Clay using LECA Replacement through Numerical Modelling
Authors: Zukri Azhani
Published: October 2021

Soil replacement technique is the simplest and oldest way in improving the soft soil under the shallow foundations. The process started by taking or removing the un-wanted problematic part of soils and replacing it with other efficient materials. Therefore, this study conducted to analyse on the soft soil replacement using Lightweight Expanded Clay Aggregate (LECA) as a filling material instead of common aggregate. LECA has been widely used in geotechnical application as the materials were successfully recognized in minimising the dead loads by more than half. The settlement magnitude of treated soft soil with LECA replacement was analysed through finite element method by using PLAXIS 2D commercial software. The prediction graph for various internal friction angle has been developed for settlement estimation The graph was then validated using developed Settlement Prediction Model, analytical equations, and numerical analysis. Another finding from this study is a decrease in the magnitude of the settlement as the internal friction angle of LECA increases.
The Effect of Interactive Computer Animation and Simulation on Students’ Achievement and Motivation in Learning Electrochemistry
Authors: Ahmad N. J. , Yakob N. , Bunyamin M. A. H. , Winarno N. , Akmal W. H.
Published: October 2021

Electrochemistry is difficult to learn due to its abstract concepts involving macroscopic, microscopic, and symbolic representation levels. Studies have shown that students can visualize and improve their understanding of chemistry by using interactive computer animation and simulation. This study reports the effect of interactive computer animation and simulation module named “Interactive Electrolysis of Aqueous Solution” (IEAS) developed to aid students in learning electrolysis. A pre and post-test control quasi-experimental design was carried out to investigate the effects of the IEAS on students’ achievement and motivation in electrochemistry topics. This study involved 62 16-years-old male students from two different secondary schools. Pre and post electrochemistry achievement tests (EAT) and pre and post- Instructional Material Motivation Surveys (IMMS) were used. For EAT, using one-way ANOVA, it shows that there was a significant difference in the post-test mean score in this study on the understanding of the electrolysis concept between students in the treatment and control groups [F (1, 60) = 5.15, p <0.05]. The qualitative results also provided evidence that the students in the treatment group had a better conceptual understanding than the control group, especially at the microscopic representation level. For the IMMS test, there was a significant difference between the treatment and control groups in terms of the mean score of the post motivation IMMS test where p <0.05 in chemistry learning [F (1,59) = 266.89, p <0.05].  Thus, it can be concluded that IEAS has an impact on enhancing the students’ understanding of the electrolysis concept, and the students are more motivated to learn electrochemistry.
The Impact of Online Mentoring in Implementing RADEC Learning to the Elementary School Teachers’ Competence in Training Students’ Critical Thinking Skills: A Case Study During COVID-19 Pandemic
Authors: Lestari H. , Sopandi W. , Sa'ud U. S. , Musthafa B. , Budimansyah D. , Sukardi R. R.
Published: October 2021

This study aims to describe the impact of online mentoring activities in implementing the RADEC (Read, Answer, Discuss, Explain, and Create) learning model on the competence of elementary school teachers in training students’ critical thinking skills. The method was a pre-experiment with a one-group pretest-posttest design involving 25 elementary school teachers in Indonesia. The teachers received online mentoring in implementing RADEC learning model. The research instrument was a questionnaire to measure teachers’ knowledge and skills in training critical thinking. The data processing technique was carried out by calculating the mean and the percentage of each item to obtain a description of the teachers’ knowledge and skills in training students’ critical thinking before and after treatment. The data were analyzed inferentially with a paired sample t-test using SPSS version 22 software to see the impact of the treatment on teachers’ competence in training critical thinking. Based on the results of the paired-sample t-test, for both the knowledge and skills aspects, the probability value (sig) was 0.00 <0.05. This result means that there was a significant difference in the knowledge and skills of teachers in training students’ critical thinking skills before and after mentoring activities. The study results indicate that the online mentoring in implementing the RADEC learning model improved teachers’ competence in training elementary school students’ critical thinking skills.
Improving Undergraduate Science Education Students’ Argumentation Skills through Debates on Socioscientific Issues
Authors: Martini M. , Widodo W. , Qosyim A. , Mahdiannur M. A. , Jatmiko B.
Published: October 2021

This research aims to examine undergraduate students’ argumentation skills during and after the learning process in the classroom setting and their responses toward the implementation of socioscientific issues (SSI) through debate in the learning process. This research involved 32 undergraduate students and implemented design-based research with pretest and posttest in a natural classroom setting using three topics of SSI debate that widely discussed in Indonesia: Nuclear Powerplant (Topic 1), Food Preservation (Topic 2), and Genetically Modified Organism (Topic 3). Data was collected using observation sheets, tests, and questionnaires. Observation is to measure argumentation ability when applying the debate method in class settings, the test measures the improvement of argumentation skills, and questionnaires measure students’ responses to the application of the debate method. In this study, argumentation scores were obtained from six indicators and divided by a maximum score of 24 times 100. Normalized gain (N-gain) was calculated to determine the effectiveness of the intervention in the classroom. T-test was also conducted to test the significance of the differences in the pretest and posttest results on argumentation skills.  The results obtained in this study are: the argumentation skills score during the learning process for six groups were 95, 80.6, 90.3, 95, 83.3, and 77.5; the mean score of pretest and posttest were 52.22 ± 6.62 and 85.78 ± 4.72. The consistency of opinions shows the change from “agree” to “disagree” for Topics 1 and 3. The undergraduate students agree and consistently agree toward Topic 2. The paired t-test result also shows that the intervention statistically has a significant difference between the two means, indicating that the undergraduate students’ argumentation skills are better than before the intervention. Otherwise, most of the undergraduate students respond positively toward the implementation of the debate related to SSI. Despite some limitations, the debate on SSI can improve argumentation skills in classroom settings, especially in science education majors.
Index of Undergraduate Students’ Attitude towards Scientific Research: A Study in Peru and Spain
Authors: Hernández R. M. , Saavedra-López M. A. , Calle-Ramirez X. M. , Rodríguez-Fuentes A.
Published: October 2021

The aim of this research was to determine the attitude towards scientific research in undergraduate university students from Peru and Spain. The research was descriptive, comparative and cross-sectional. The sample consisted of 953 undergraduate students currently enrolled in universities in Spain (485) and Peru (468), and the information was collected through convenience sampling. The General Index of Attitude towards Research instrument was applied, which was adapted for the study. Its statistical validation was carried out and high reliability of the instrument was proved with a Cronbach's Alpha of 921. According to the questionnaire scores, a sociodemographic survey was also applied. Regarding the results, it was found that students from Peru have a high predisposition towards research (51.5%) compared to students from Spain (23.5%). Regarding knowledge about research, students in both countries recognize that scientific research is not adequately valued (60.6% in Spain and 54.3% in Peru); however, they would like to carry out educational scientific research (63.3% and 71.2, respectively). Regarding the evaluation of the quality of university education, undergraduate students from Spain perceive a better quality in their education (7.22 out of 10), quality of the program in which they are enrolled (7.31 out of 10), quality of fellow students (7.46 out of 10), and welfare and infrastructure services (7.30 out of 10). It is concluded that students from Peru show a better attitude towards research (M=28.98, DT=10.26) than students from Spain (M=22.61, DT=8.28).
The Validation of Digital Analysis Tool-Assisted Real-World Inquiry (Digita-RI) as a Modification of the Inquiry-Based Learning Model in the Digital Age
Authors: Nurohman S. , Sunarno W. , Sarwanto S. , Yamtinah S.
Published: October 2021

Inquiry-based learning has been tested to improve conceptual understanding, reduce misconceptions, and provide students with experiences in scientific work. However, in its implementation, inquiry-based learning is often faced with scientific facts from the real world with data which hard to analyze using traditional methods. Therefore, a breakthrough is needed to overcome the weaknesses of inquiry-based learning by integrating digital analysis tools and the concept of real-world learning. This integration produces a new learning model, the Digital Analysis Tool-Assisted Real-World Inquiry (Digita-RI). This study aims to test the feasibility and practicality of the Digita-RI learning model. This Research and Development (R&D) use the steps proposed by Barg and Gall. The feasibility test of the Digita-RI model was carried out through the Focus Group Discussion (FGD) method and the assessment of the Digita-RI model book involving seven experts. The practicality test was carried out through the Think Aloud Protocol (TAP), and the assessment of the Digita-RI model guidebook involved five practitioner lecturers and six students. The results of expert, practitioner, and user assessments were analyzed using the Aiken coefficient (Aiken’s V). The results showed that Digita-RI is a feasible and practical learning model. Therefore, it can be concluded that Digita-RI has the feasibility and practicality to be used in science learning in the classroom.
Improving Elementary School Students’ Critical Thinking Skill in Science through HOTS-based Science Questions: A Quasi-Experimental Study
Authors: Sidiq Y. , Ishartono N. , Desstya A. , Prayitno H. J. , Anif S. , Hidayat M. L.
Published: October 2021

There have been many efforts to improve elementary school students’ critical thinking skills in science through various learning methods. However, only a few research results show efforts to improve critical thinking skills through HOTS-based science questions for elementary school students. Therefore, the purpose of this study is to test the effectiveness of student habituation with HOTS-based science questions in improving elementary school students’ critical thinking skills in science. Quasi-experimental methods were employed in this research with a nonequivalent control group design involving a treatment class and a control class. The treatment class gets treatment in HOTS-based science questions habituation during the learning process, while the control class in conventional approaches. A total of 60 students is from one of the elementary schools in Surakarta, Indonesia. To take data related to students’ critical thinking skills, they were given pretest and posttest where each test used HOTS-based science questions in an essay. The obtained data from the tests were then analyzed using descriptive and inferential statistical techniques. This study showed that the average of critical thinking skills in science of students in the experimental class was higher than the control class, with a positive mean difference of 0.4226. Based on these results, it is recommended that the results of this study can provide an overview to educational practitioners at the elementary school level and researchers in the field of science education related to efforts to improve elementary school students’ critical thinking skills in science through the habituation of HOTS-based science questions.
Medullary thyroid carcinoma (MTC): unusual metastatic sites
Authors: Kazakou Paraskevi , Simeakis George , Alevizaki Maria , Saltiki Katerina
Published: October 2021

Medullary thyroid carcinoma (MTC) has a varying clinical course; distant metastases are frequently present even at diagnosis. We present two MTC cases with unusual metastatic sites. Two female patients are presented with slow progressive MTC. The first case developed distant metastases 23 years after diagnosis and underwent locoregional therapies. At the same time a breast mass developed representing MTC metastasis. Treatment with vandetanib led to long-term disease stabilization. The second patient is presented with metastases in the pancreas 13 years after diagnosis. Shortly, a painful mass developed in the mandible and metastasis of MTC was diagnosed. Disease progression was recorded 20 months after the initiation of local and systemic therapy. Such cases have only rarely been reported in the literature and highlight the need for prompt recognition of unexpected MTC metastases.

Learning points

Unusual sites of metastasis may appear in patients with medullary thyroid carcinoma (MTC) years after the initial diagnosis.

Although rare, unexpected MTC metastases highlight the need for prompt recognition and appropriate treatment.

Local recurrences accompanied by inappropriately low calcitonin levels should prompt further investigation for possible distant metastatic disease.

Systemic treatment with tyrosine kinase inhibitors may be effective even in patients with unusual metastases from MTC.
Adipose tissue immune cells in obesity, type 2 diabetes mellitus and cardiovascular diseases
Authors: Cinkajzlová Anna , Mráz Miloš , Haluzík Martin
Published: October 2021

Immune cells are an inseparable component of adipose tissue intimately involved in most of its functions. Physiologically, they regulate adipose tissue homeostasis, while in case of adipose tissue stress, immune cells are able to change their phenotype, enhance their count and subsequently contribute to the development and maintenance of local adipose tissue inflammation. Immune cells are an important source of inflammatory cytokines and other pro-inflammatory products that further influence not only surrounding tissues but via systemic circulation also the whole organism being thus one of the main factors responsible for the transition from simple obesity to associated metabolic and cardiovascular complications. The purpose of this review is to summarize current knowledge on different adipose tissue immune cell subsets and their role in the development of obesity, type 2 diabetes mellitus and cardiovascular diseases.
A Dating Violence Prevention Program for Middle School Youth: A Cluster Randomized Trial
Authors: Temple Jeff R. , Baumler Elizabeth , Wood Leila , Thiel Melanie , Peskin Melissa , Torres Elizabeth
Published: October 2021

OBJECTIVES

We conducted a cluster randomized controlled trial to test the a priori hypothesis that students attending an intervention middle school would be less likely to report physical adolescent relationship abuse (ARA) 1 year later compared with students attending a control school. Secondary objectives were to determine if the intervention reduced substance misuse, bullying, and fighting.

METHODS

Twenty-four Texas public middle schools were matched by the size of student enrollment, number of economically disadvantaged students, and race and ethnicity of the student body and randomly assigned to the intervention (n = 12; 1237 participants) or the control (n = 12; 1531participants) group. The intervention, Fourth R, is a classroom-based curriculum delivered by existing teachers and consists of 21 lessons on injury prevention, substance use, and growth and development.

RESULTS

Participants (50% female) self-reported ethnicity as Hispanic or Latinx (35%), Black or African American (24%), Asian American (17%), White (8%), and multiethnicity or other (16%). Among those who have dated, students in the intervention schools were less likely to report perpetrating physical ARA (intervention = 14.9% versus control = 18.3%) relative to students in the control schools (adjusted odds ratio, 0.66; 95% confidence interval, 0.43–1.00; P = .05). In the overall sample, no significant differences emerged between control and intervention groups with respect to substance misuse, fighting, and bullying.

CONCLUSIONS

The middle school version of Fourth R is effective in reducing physical ARA perpetration over at least 1 year. The intervention did not have an effect on bullying perpetration, physical fighting with peers, and substance misuse. Long-term assessment, especially follow-up that covers the transition to high school, is needed to examine the program benefit on key outcomes.
Off-Label Prescription of COVID-19 Vaccines in Children: Clinical, Ethical, and Legal Issues
Authors: deSante-Bertkau Jennifer E. , Knilans Timothy K. , Persad Govind , Zettler Patricia J. , Lynch Holly Fernandez , Antommaria Armand H. Matheny
Published: October 2021

The US Food and Drug Administration (FDA) approval of the biologics license application for the Pfizer-BioNTech coronavirus disease 2019 vaccine (Comirnaty) on August 23, 2021, opened the door to the off-label vaccination of children younger than the age range currently covered by either the biologics license application (16 years old and older) or the emergency use authorization (12 to 15 years old). Although prescribing medications at doses, for conditions, or in populations other than those approved by the FDA is generally legal and is common in pediatrics, the FDA, the Centers for Disease Control and Prevention, and the American Academy of Pediatrics have recommended against off-label prescription of the coronavirus disease 2019 vaccine. Several commentaries consider a case in which parents ask their child’s pediatrician to prescribe the vaccine for their 11-year-old with special health care needs before approval or authorization in her age group. The first commentary considers the potential benefits and risks to the patient, as well as to the family, the provider, and society, emphasizing the unknown risks in younger patients and the need for adequate informed consent. The second commentary describes an algorithm and principles for evaluating off-label prescribing and argues that the current benefits of prescribing Comirnaty off label to children <12 do not outweigh the risks. The third commentary addresses ethical and legal issues, ultimately calling on federal agencies to remove legal barriers to making the vaccine available to children in age groups that currently lack authorization.
Grey Signal Predictor and Fuzzy Controls for Active Vehicle Suspension Systems via Lyapunov Theory
Authors: Chen Tim , Hung Chih Ching , Huang Yu Ching , Chen John C.Y. , Rahman Samiur , Islam Mozumder Towfiqul
Published: October 2021

In order to investigate and decide that the vehicle asymptotic vibration stability and improved comfort, the present paper deals with a fuzzy neural network (NN) evolved bat algorithm (EBA) backstepping adaptive controller based on grey signal predictors. The Lyapunov theory and backstepping method is utilized to appraise the math nonlinearity in the active vehicle suspension as well as acquire the final simulation control law in order to track the suitable signal. The Discrete Grey Model DGM (2,1) have been thus used to acquire prospect movement of the suspension system, so that the command controller can prove the convergence and the stability of the entire formula through the Lyapunov-like lemma. The controller overspreads the application range of mechanical elastic vehicle wheel (MEVW) as well as lays a favorable theoretic foundation in adapting to new wheels.
An Approximation of Label Distribution-Based Ensemble Learning Method for Online Educational Prediction
Authors: Zhang Long , Kai Shu , Keyu Huang , Ruiqiu Zhang
Published: October 2021

Online education becomes increasingly important since traditional learning is shocked heavily by COVID-19. To better develop personalized learning plans for students, it is necessary to build a model that can automatically evaluate students’ performance in online education. For this purpose, in this study we propose an ensemble learning method named light gradient boosting channel attention network (LGBCAN), which is based on label distribution estimation. First, the light gradient boosting machine (LightGBM) is used to predict the performance in online learning tasks. Then The Channel Attention Network (CAN) model further improves the function of LightGBM by focusing on better results in the K-fold CrossEntropy of LightGBM. The results are converted into predicted classes through post-processing methods named approximation of label distribution to complete the classification task. The experiments are employed on two datasets, data science bowl (DSB) and answer correctness prediction (ACP). The experimental results in both datasets suggest that our model has better robustness and generalization ability.
Construction Method of Tender Document Based on Case-based Reasoning
Authors: Zhou Tingting , Gao Xuedong , Wei Guiying
Published: October 2021

The core activities of tender documents compilation are to collect similar historical tender documents, select compilation templates of tender documents and revise templates of tender documents partially. However, when the historical tender documents have accumulated to a certain amount, it becomes extremely difficult for compilers to summary, reuse and revise templates artificially in traditional compiling methods. Based on casebased reasoning (CBR), this paper studied the content recommendation method in the process of tender document construction. Firstly, a structured model of tender documents was constructed, and similar tender cases were retrieved from the tender case database according to the characteristics of tender cases; Secondly, the non-interference sequence index was used to measure the similarity of clauses used in similar tender cases, and the recommended sequences of reference template and content module of tender documents were constructed, which realized the recommendation of compiling templates of tender documents and partial revision of templates; Finally, the knowledge of the new tender case was updated. The empirical analysis shows that the construction method of tender documents based on case-based reasoning not only proposes a suitable strategy for compiling tender documents, but also improves the compilation efficiency of tender documents.
Screening Key Indicators for Acute Kidney Injury Prediction Using Machine Learning
Authors: Wang Jiaming , Zhu Bing , Liu Pei , Jia Ruiqi , Jia Lijing , Chen Wei , Feng Cong , Li Jing
Published: October 2021

Acute kidney injury is a common critical disease with a high mortality. The large number of indicators in AKI patients makes it difficult for clinicians to quickly and accurately determine the patient’s condition. This study used machine learning methods to filter key indicators and use key indicator data to achieve advance prediction of AKI so that a small number of indicators could be measured to reliably predict AKI and provide auxiliary decision support for clinical staff. Sequential forward selection based on feature importance calculated by XGBoost was used to screen out 17 key indicators. Three machine learning algorithms were used to make predictions, namely, logistic regression (LR), decision tree, and XGBoost. To verify the validity of the method, data were extracted from the MIMIC III database and the eICU-CRD database for 1,009 and 1,327 AKI patients, respectively. The MIMIC III database was used for internal validation, and the eICU-CRD database was used for external validation. For all three machine learning algorithms, the prediction performance from using only the key indicator dataset was very close to that from using the full dataset. The XGBoost algorithm performed the best, and LR was the next best. The decision tree performed the worst. The key indicator screening method proposed in this study can achieve a good predictive performance while streamlining the number of indicators.
A Boundary Determined Neural Model for Relation Extraction
Authors: TANG RUI XUE
Published: October 2021

Existing models extract entity relations only after two entity spans have been precisely extracted that influenced the performance of relation extraction. Compared with recognizing entity spans, because the boundary has a small granularity and a less ambiguity, it can be detected precisely and incorporated to learn better representation. Motivated by the strengths of boundary, we propose a boundary determined neural (BDN) model, which leverages boundaries as task-related cues to predict the relation labels. Our model can predict high-quality relation instance via the pairs of boundaries, which can relieve error propagation problem. Moreover, our model fuses with boundary-relevant information encoding to represent distributed representation to improve the ability of capturing semantic and dependency information, which can increase the discriminability of neural network. Experiments show that our model achieves state-of-the-art performances on ACE05 corpus.
Vehicle Speed Estimation Using Gaussian Mixture Model and Kalman Filter
Authors: Tayeb Ahmed Abdulwahab , Aldhaheri Rabah Wasel , Hanif Muhammad Shehzad
Published: October 2021

Many countries use traffic enforcement camera to monitor the speed limit and capture over speed violations. The main objective of such a system is to enforce the speed limits which results in the reduction of number of accidents, fatalities, and serious injuries. Traditionally, the task is carried out manually by the enforcement agencies with the help of specialized hardware such as radar and camera. To automate the process, an efficient and robust solution is needed. Vehicle detection, tracking and speed estimation are the main tasks in an automated system which are not trivial. In this paper, we address the problem of vehicle detection, tracking, and speed estimation using a single fixed camera. A background subtraction method based on the Gaussian Mixture Model (GMM) is employed to detect vehicles because of its capability in dealing with complex backgrounds and variations in the appearance due to illumination and scale. Next, the detected vehicles are tracked in each frame by using the Kalman Filter. Finally, an estimate the speed of each vehicle is determined by using the perspective geometry model. The complete system is tested at our university campus and the results are promising.
Video Streaming Service Identification on Software-Defined Networking
Authors: Castañeda Herrera Luis Miguel , Campo-Muñoz Wilmar Yesid , Torres Alejandra Duque
Published: October 2021

It is well known that video streaming is the major network traffic today. Futhermore, the traffic generated by video streaming is expected to increase exponentially. On the other hand, SoftwareDefined Networking (SDN) has been considered a viable solution to cope with the complexity and increasing network traffic due to its centralised control and programmability features. These features, however, do not guarantee that network performance will not suffer as traffic grows. As result, understanding video traffic and optimising video traffic can aid in control various aspects of network performance, such as bandwidth utilisation, dynamic routing, and Quality of Service (QoS). This paper presents an approach to identify video streaming traffic in SDN and investigates the feasibility of using Knowledge-Defined Networking (KDN) in traffic classification. KDN is a networking paradigm that takes advantage of Artificial Intelligence (AI) by using Machine Learning approaches, which allows integrating behavioural models to detect patterns, like video streaming traffic identification, in SDN traffic. In our initial proof-of-concept, we derive the relevant information of network traffic in the form of flows statistics. Then, we used such information to train six ML models that can classify network traffic into three types, Video on Demand (VoD), Livestream, and no-video traffic. Our proof-of-concept demonstrates that our approach is applicable and that we can identify and classify video streaming traffic with 97.5% accuracy using the Decision Tree model.
Development and Analysis of Low-Cost IoT Sensors for Urban Environmental Monitoring
Authors: Muntean Ionut , Mois George Dan , Folea Silviu Corneliu
Published: October 2021

The accelerated pace of urbanization is having a major impact over the world’s environment. Although urban dwellers have higher living standards and can access better public services as compared to their rural counterparts, they are usually exposed to poor environmental conditions such as air pollution and noise. In order for municipalities and citizens to mitigate the negative effects of pollution, the monitoring of certain parameters, such as air quality and ambient sound levels, both in indoor and outdoor locations, has to be performed. The current paper presents a complete solution that allows the monitoring of ambient parameters such as Volatile Organic Compounds, temperature, relative humidity, pressure, and sound intensity levels both in indoor and outdoor spaces. The presented solution comprises of low-cost, easy to deploy, wireless sensors and a cloud application for their management and for storing and visualizing the recorded data.
Verification of University Student and Graduate Data using Blockchain Technology
Authors: Shakan Yassynzhan , Kumalakov Bolatzhan , Mutanov Galimkair , Mamykova Zhanl , Kistaubayev Yerlan
Published: October 2021

Blockchain is a reliable and innovative technology that harnesses education and training through digital technologies. Nonetheless, it has been still an issue keeping track of student/graduate academic achievement and blockchain access rights management. Detailed information about academic performance within a certain period (semester) is not present in the official education documents. Furthermore, academic achievement documents issued by institutions are not secured against unauthorized changes due to the involvement of intermediaries. Therefore, verification of official educational documents has become a pressing issue owing to the recent development of digital technologies. However, effective tools to accelerate the verification are rare as the process takes time. This study provides a prototype of the UniverCert platform based on a consortium version of the decentralized, open-source Ethereum blockchain technology. The proposed platform is based on a globally distributed peer-to-peer network that allows educational institutions to partner with the blockchain network, track student data, verify academic performance, and share documents with other stakeholders. The UniverCert platform was developed on a consortium blockchain architecture to address the problems universities face in storing and securing student data. The system provides a solution to facilitate students’ registration, verification, and authenticity of educational documents.
Obese Frailty and Combined Exercise
Authors: Lee Hae Sung , Kim Jong-Hee
Published: October 2021

PURPOSE: Frailty is a geriatric syndrome that impairs the health and quality of life of older adults. While unintended weight loss is known to be a primary risk factor for frailty, obesity has also been closely associated with frailty. Combined exercise is thought to be an effective way of resolving obesity and frailty, but studies demonstrating the effect of combined exercise on obese frailty are lacking. In this review, we seek to understand the relevant mechanisms by exploring prior studies on obese frailty, and provide the implications of appropriate combined exercise interventions for obese frailty.METHODS: To collect data for this study, we used academic search systems such as Scopus, Google Scholar, PubMed, and Web of Science. The keywords used for the search were a combination of words such as ’obesity’, ‘frailty’, ‘combined or multicomponent exercise’, and ‘older or elderly adults’.RESULTS: The results from the 16 selected articles confirmed that combined exercise reduces body weight, percentage of body fat, and risk of falls. Moreover, it improves muscle strength, balance, and walking function of the obese frail population.CONCLUSIONS: As we have confirmed the positive outcomes on the combined exercise for obese frail older adults, an optimal exercise program needs to be presented. Older adults with obesity are recommended to exercise at least 2-3 times a week during the initial period. Further, they should begin with low-intensity walking, full-body exercise, balance, and flexibility exercises, then gradually increase the exercise volume. Moreover, to facilitate the positive outcomes of physical training and to encourage autonomy and enjoyment of exercise among obese frail older adults, a novel method and an individualized scientific exercise program need to be developed.
Awareness of Competences and Teacher Education Plan that Special Education Experts should have to Prepare for the Era of Intelligent Information Revolution
Authors:   The Korean Society of Special Education, Kang Eunyoung
Published: October 2021

The purpose of this study is to bring awareness towards the capabilities of future societies; that special education experts will need to prepare a plan to accommodate for potential technological enhancements, as the era of intelligent information approaches. A total of eight special teachers; as well as general teachers, professors, and big data experts; were conducted through numerous 1:1 in-depth interviews in order to analyze the results. The results were largely divided into servant-leadership competency, as well as future-oriented job competency; this is due to the high-level competencies that special teachers must acquire in the era of the Intelligent Information Revolution. In the servant-leadership competency, the competency between facilitators will assist in learning. The competency of both flexible thinking and communication linking are based on specialized knowledge. The ability to execute data-based decision making and individualized education were derived as sub competencies. In the future-oriented job competency, data processing, and interpretation competency; the ability to understand and use advanced technology, affect sensibility, and human dignity detection capabilities were derived. These results add up to a total of six basic competencies and two advanced competencies. Based on these results, a three-step plan was proposed in order to enhance the capabilities that will be required for special education experts in the future. Because of this, contents that are necessary for future research were discussed.