bluuebunny/crossref_metadata_2025 huggingface dataset:
Acute caffeine supplementation improves jumping, sprinting, and change‐of‐direction performance in basketball players when ingested in the morning but not evening
Authors: Stojanović Emilija , Scanlan Aaron T. , Milanović Zoran , Fox Jordan L. , Stanković Ratko , Dalbo Vincent J.
Published: January 2021

This study compared the effects of acute caffeine supplementation (3 mg/kg) administered in the morning and evening on performance‐related variables in basketball players. Eleven, national‐level, adolescent male basketball players underwent field‐based fitness testing on four occasions: morning (10:00) with caffeine ingestion (AMCAFF), morning (10:00) with placebo ingestion (AMPLAC), evening (21:00) with caffeine ingestion (PMCAFF), and evening (21:00) with placebo ingestion (PMPLAC). Fitness testing included of a countermovement jump without arm swing (CMJ), CMJ with arm swing (CMJAS), squat jump (SJ), Lane Agility Drill (LAD), 20‐m linear sprint, and Suicide Run with (SRD) and without dribbling (SR). Data were analysed using two‐way repeated measures analyses of variance and paired t‐tests, with effect sizes (ES) also determined for all pairwise comparisons. Follow‐up t‐test comparisons revealed that AMCAFF produced small‐moderate, significant (p<0.001), improvements in CMJ (ES = 0.51), CMJAS (ES = 0.40), SJ (ES = 0.51), and SR (ES = −0.45) compared to AMPLAC. AMCAFF also produced a moderate, significantly (p<0.001) faster LAD (ES = −0.61) compared to PMCAFF. PMPLAC demonstrated small‐moderate, significant (p<0.05) improvements in CMJ (ES = 0.43), CMJAS (ES = 0.48), and 20‐m sprint (ES = −0.63) compared to AMPLAC. In contrast, AMPLAC resulted in large, significantly (p<0.001), faster SRD (ES = −1.46) and SR (ES = −1.59) compared to PMPLAC. Given the ergogenic effects of caffeine during basketball‐specific fitness tests appear to be influenced by time of ingestion, basketball practitioners should consider administering caffeine only to players in the morning to improve vertical jump, sprinting, and change‐of‐direction performance, with no beneficial effects observed with caffeine ingestion in the evening.

Highlights

The effect of caffeine supplementation on basketball‐specific performance related variables were mediated by ingestion time in elite, adolescent basketball players.

AMCAFF produced small‐moderate improvements in vertical jump, change‐of‐direction, 20‐m linear sprint, and repeated‐sprint performance compared to AMPLAC while PMCAFF produced trivial differences in each performance‐related variable compared to PMPLAC.

Comparisons between ingestion times in the placebo condition revealed vertical jump height and 20‐m sprint speed were impaired in the morning compared to the evening, but these time‐dependent differences were eliminated when caffeine was consumed in the morning.

Basketball practitioners should consider administering caffeine only to players in the morning to improve vertical jump, sprinting, and change‐of‐direction performance, with no beneficial effects observed with caffeine ingestion in the evening.
Sedentary behaviours and their relationship with body composition of athletes
Authors: Júdice Pedro B. , Hetherington‐Rauth Megan , Magalhães João P. , Correia Inês R. , Sardinha Luís B.
Published: January 2021

During the recovery period, athletes present high sedentary behaviour (SB). In non‐athletes, there is a direct relationship between SB and obesity. However, little is known about this relationship in athletes. We hypothesized that different types of SB entail different associations with body composition outcomes.

We examined the associations between different types of SB and body composition outcomes in 135 athletes (70 males) aged 21.3 ± 3.9 years old. Dual‐energy X‐ray absorptiometry was performed to assess fat mass (FM), fat‐free mass (FFM) and trunk fat mass (TFM). A validated SB questionnaire (PACE) was used to estimate total SB and specific sedentary pursuits on an average day. Multiple linear regression analyses were performed, adjusting for age, sex, weekly training time, years of sport practice, and sport type.

A positive association was found for total SB and total screen time with %TFM (β = 0.220, p = 0.038 and β = 0.319, p = 0.040, respectively), while an inverse association was found for %FFM (β = −0.214, p = 0.042 and β = −0.310, p = 0.026). A higher total screen time was related with a higher %FM (β = 0.283, p = 0.035). With a much stronger effect size, cell phone screen time was positively related with %FM (β = 1.447, p = 0.001).

There is still debate whether high levels of physical activity can fully counteract the harms of SB. These findings suggest that SB, particularly cell phone screen time, can compromise athletes’ body composition, regardless of weekly training time. Sport federations and coaches may improve athletes’ body composition by targeting specific sedentary pursuits, i.e. total screen time and cell phone screen time, during athletes’ recovery time.

Highlights

Even in athletes, SB can compromise total and regional body composition regardless of high training time.

Screen time, specifically cell phone screen time seems to be the sedentary pursuit to target in athletes.

Sport federations and coaches must control SB during athletes' recovery time.
Beliefs, perceived risk, obstacles and intention to act. An explanatory model for mitigation and coping behaviours regarding climate change (Creencias, percepción de riesgo, obstáculos e intención de actuar. Un modelo explicativo de conductas de mitigación y afrontamiento ante el cambio climático)
Authors: Barrera-Hernández Laura-Fernanda , Corral-Verdugo Víctor , Echeverría-Castro Sonia-Beatriz , Sotelo-Castillo Mirsha-Alicia , Ocaña-Zúñiga Jesús
Published: January 2021

Mitigation behaviours regarding climate change are actions that seek to halt or reduce greenhouse gas emissions. Adaptive responses, on the other hand, are coping reactions to this phenomenon. The research presented here tested out an explanatory model for mitigation behaviours and coping reactions in response to the phenomenon of climate change (perceived risk and impact on the environment and health) based on beliefs regarding CC, obstacles to protect oneself from this phenomenon and intention to act. A total of 370 people from two Mexican cities took part in the research. The findings, processed by a structural equations model, show that beliefs regarding CC influence coping responses and intention to act, which in turn positively impact mitigation behaviours in response to CC. Beliefs regarding CC did not affect the perception of obstacles to protect oneself from climate change. Furthermore, the perception of obstacles and coping responses similarly did not influence intention to act.
54 W nanosecond Yb-doped all-fiber amplifier at ultra-high repetition rate (tens of MHz) based on mode-locked fiber oscillator and single-mode fiber stretcher
Authors: Yang Min , Li Pingxue , Li Shun , Xiong Wenhao , Wang Kaixuan , Yao Chuanfei , Wang Dongsheng
Published: January 2021

We report on a nanosecond all-fiber amplifier with repetition rate of tens of MHz. It is based on a passively mode-locked fiber oscillator at 1064 nm, which has a pulse width of 28 ps and repetition rate of 27.7 MHz. The single-mode fiber with length of 8 km is adopted as a fiber stretcher, in which new frequency components are introduced by strong nonlinear effect such as self-phase modulation, resulting in the broadening of spectral bandwidth from 0.4 nm to around 20 nm. The group-velocity dispersion of the 8 km fiber stretcher is −38 ps (nm km) −1, which stretches the pulse duration of the picosecond pulse to 1–7 ns. At the repetition rate of 27.7 MHz, an average power of 54 W is demonstrated with pulse width of 1.3 ns, and 21 W is achieved with pulse width of ∼5 ns, which have optical-to-optical conversion efficiencies of 41.2% and 30.1% respectively. This all-fiber amplifier based on the passively mode-locked fiber oscillator and 8 km single-mode fiber stretcher is capable of delivering nanosecond pulses while maintaining an ultra-high repetition rate of tens of MHz.
In-situ analyzing of air pollution by laser induced breakdown spectroscopy in laser paint removal
Authors: Deng Guoliang , Zhou Qionghua
Published: January 2021

Laser paint removal is widely used in industry in recent years. Compared with traditional paint removal methods, laser paint removal is considered clean and environmentally-friendly. However, particles generated in the cleaning process may cause significant air pollution and harm to the operator’s health. In this work, we demonstrated that particles with different sizes, especially those smaller than 2.5 μm, are generated in the process of laser paint removal. The chemical composition of these particles is analyzed in-situ by using laser induced breakdown spectroscopy. The results show that heavy metal elements (such as Ba, Pb and Ti) can be found in the particles. These heavy metal elements containing, small size particles pollute the air to an unacceptable level. We suggest that great attention should be taken to deal with this particulate air pollution to reduce the health risk for laser paint removal workers.
Posted prediction in social media base on Markov chain model: twitter dataset with covid-19 trends
Authors: Suryaningrat W , Munandar D , Maryati A , Abdullah A S , Ruchjana B N
Published: January 2021

The influence of social media is very attractive in disseminating information; even social media analysis is one of the focuses in the field of research in terms of data mining. In its development not only the field of social science that exists but many studies of social media that can be solved stochastically to calculate the trend of the emergence of a discussion on social media. In this paper, we investigated calculations and predictions using Markov Chains on the emergence of discussions on Twitter media related to coronavirus disease tweets or better known as covid-19. The tweet data obtained is a random sample of the tweet posts that are crawled at the specified time. The tweet data is crawled at three different observations each day for thirteen days continuously. The results of data crawling are calculated to determine the transition from one observation to the next observation. The stages of the process are; crawling tweet data with keywords coronavirus and covid-19; data cleaning process; data processing; Markov Chain modeling; n-step distribution and long-term prediction; interpretation of results. The computational results used are opportunity distribution conditions for the number of tweets. As a transition between two states, namely low (0) and high (1) relative to mean or median. The results of the opportunity distribution obtained in the next 145-time steps (0.28767, 0.71233) and (0.47368, 0.52632) in the probability distribution of the number of tweets are respectively the mean and median values. The results of the modeling show that the conversation on Twitter for 145-time steps in the next prediction is estimated to remain high along with the outbreak of coronavirus or covid-19 before this epidemic subsides.
The application of k-nearest neighbors classifier for sentiment analysis of PT PLN (Persero) twitter account service quality
Authors: Damarta R , Hidayat A , Abdullah A S
Published: January 2021

Social media has an important role in human life. In its implementation social media is used as a media for opinion and self-expression. One of the social media that is often used in Indonesia is Twitter. PT PLN (Persero) as a State-Owned Enterprise that is engaged in providing electricity always tries to provide optimal services. The text mining method can be used to control PT PLN (Persero) service quality by classifying Twitter data with the k-Nearest Neighbors algorithm. Text mining is used to extract information from unstructured textual data to produce useful information. Data classification is a text mining application for information retrieval. In this study the data collected will pass the preprocessing stage, using the k-Nearest Neighbors algorithm to classify data into negative, neutral, or positive classes. The data used in this study was sourced from Twitter. Data is taken from 1 December 2019 to 1 February 2020 using the Twitter API with the keyword ‘@ pln_123’. We obtained 3,000 tweet data successfully. The results are implemented in web-based applications that are built using the Python programming language. Evaluation of the k-Nearest Neighbors model produces an accuracy value of 87.41%. The classification prediction results also show that there is a tendency of the positive sentiment of 35%, the neutral sentiment of 28%, and the negative sentiment of 37%.
Invariant moment and learning vector quantization (LVQ NN) for images classification
Authors: Widagda I G A , Sastra N P , Wiharta D M , Hartati R S
Published: January 2021

Image classification need two main components, i.e., features and classifier. The feature commonly used for classification of images with different scale is invariant moment; its value is invariant against the spatial transformation dealing with translation, scale and rotation. The classifier that is widely used for classification is LVQ NN. It is shallow network containing only two layers, the initial value of its weight is more fixed so that its output is more stable and its algorithm is relatively simple thus both training and testing process are run fast. Based on these facts, therefore, this research proposed a combination method of invariant moment and LVQ NN (IM-LVQ). The ability of the proposed method would be compared with two other methods. Firstly, the combination method of invariant moment and Euclidean distance (IM-ED). Secondly, the combination of invariant moment and principal component analysis (IM-PCA). The performance of the three methods was evaluated quantitatively with several metrics, viz.: Confusion Matrix, Accuracy, Precision, True Positive Rate, False Positive Rate, ROC graph and training time. The evaluation of the metrics was based upon the changing (reduction) of the scale/size of training image. The results showed that IM-LVQ method outperformed the other two methods in aforementioned metrics.
Analysis of membership function in implementation of adaptive neuro fuzzy inference system (ANFIS) method for inflation prediction
Authors: Raharja M A , Darmawan I D M B A , Nilakusumawati D P E , Supriana I W
Published: January 2021

This research will analyze which fuzzy membership function (MF) gives the best results in the implementation of the Adaptive Neuro-fuzzy inference system (ANFIS) method. The case study conducted is to predict the growth of inflation in Bali Province with ANFIS which has the main objective of analyzing the fuzzy membership function and designing a model that can predict the value of inflation growth. Inflation can also be defined as a process of increasing general prices or decreasing the value of money continuously. Inflation growth prediction uses the ANFIS method with five input parameters in the form of regional economic indicators, and the number of pairs of initial data used is 34 annual periods. Several types of membership functions (MF) that will be tested and analyzed are triangular MF, MF trapezium, and MF gbell. The cryptic inference system used is TSK-Order One, and the learning method used is a hybrid method. Based on the research results, the analysis of the fuzzy membership function in the inflation prediction system produces the best error is 1.35E-07 with the type of triangular membership function (MF).
Detection and description generation of diabetic retinopathy using convolutional neural network and long short-term memory
Authors: Amalia R , Bustamam A , Sarwinda D
Published: January 2021

Diabetic Retinopathy (DR) is one of the eye diseases suffered by diabetes patients that will cause blindness if it does not get effectively treated for a certain period of time. Early detection is needed to help patients get effective treatment based on their severity. Researchers have done copious amounts of research regarding the methods for DR detection using shallow learning and deep learning approaches. The proposed method in this paper is a combination of two deep learning architectures, namely Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM). CNN is used to detect lesions on retinal fundus images, and LSTM is used for generating description sentences based on those lesions. In the training and testing process, the CNN output will be used for the input of LSTM. The training process’s target is to produce a model that can map retinal fundus images into a sentence. The results of this experiment using the MESSIDOR data set has an accuracy of around 90%.
Ethno-informatics for anthroponymy classification in Sumedang District using data mining
Authors: Abdullah A S , Rejito J , Pradana A , Zakaria M M , Permana F C , Ruchjana B N
Published: January 2021

Ethnoscience is used to look at culture from a scientific perspective, helping to understand how to develop different forms of knowledge and beliefs. One of the fields studied in Ethnoscience is Ethno-informatics, which is the application of informatics in culture. The methodology used is the process of knowledge discovery in databases in data mining, the process of automatically extracting knowledge from large databases, to get interesting patterns so that knowledge can be obtained. The application of anthroponymy by exploring the population database in Sumedang district, the results of the 2019 census from the Sumedang District Population Office. Then the anthroponymy application was developed in Sumedang district. The results of data processing show that the top ten names of people who are most used or most favorite in Sumedang district are: Muhammad, Muhamad, Asep, Siti, Agus, Dede, Ade, Ai, Tati, Dadang. Muhammad’s name has been a favorite since 2000 until now 2020. Meanwhile, the top ten favorite names that have just appeared in the last ten years (2010-2020) are sorted based on ranking including; Naura, Arsyla, Keyla, Raffa, Rafka, Aqila, Zahra, Keusha and Alesha. In general, the Sundanese name in Sumedang district is still widely used, but generally it is relatively down-to-earth, replaced by new names as an uptake of other cultural names. Changes in self-naming in Sumedang regency in particular, generally self-names in Sundanese culture in West Java, were caused by the rapid development of information and communication technology. This research is expected to provide input for the community, especially for the younger generation as a guide in their daily life. It takes a significant effort from the government to maintain it, so that local culture and wisdom, especially the naming of people in Sumedang district, generally Sundanese culture can be well preserved.
Implementation of audio recognition using mel frequency cepstrum coefficient and dynamic time warping in wirama praharsini
Authors: Wibawa I D G Y A , Darmawan I D M B A
Published: January 2021

Sekar Agung or wirama is a Balinese classic work which contains of moral values, and is usually sung during traditional or religious ceremonies. The classic nature of wirama made this art was abandoned by the younger generation who were less interested to learn or preserve it. Related to the problem, this study aimed at conducting sound matching as a medium to learn wirama praharsini based on the rule of guru and laghu. Wirama Praharsini was chosen because of the simple way of singing and pronunciation when it was compared to the other kinds of wirama. This study applied voice recognition method to identify words’ pronunciation in wirama praharsini. MFCC (Mel Frequency Cepstrum Coefficient) was used to extract the voice feature from expert and the tester. The extraction results were compared with the DTW (Dynamic Time Warping) method that was used to compare two sound features from MFCC process. The result of this study showed average accuracy value of 88.89% which indicated that the implementation of MFCC and DTW method could be done to recognize the wirama praharsini pronunciation and detect the right way to sing it based on the rules of guru and laghu in wirama.
Extreme gradient boosting (XGBoost) method in making forecasting application and analysis of USD exchange rates against rupiah
Authors: Islam S F N , Sholahuddin A , Abdullah A S
Published: January 2021

Economic conditions in Indonesia are still unstable, causing the US dollar exchange rate to increase. This is because most international transactions in Indonesia use US dollars. Prediction or forecasting is chosen as one of the important things in choosing a market to invest in buying and selling. This research will focus on making forecasting applications and analyzing the exchange rate of USD against rupiah based on time series data or temporal datasets from the Investing.com site using machine learning methods, namely Extreme Gradient Boosting (XGBoost). Applications created using the python programming language and streamlit framework. Modeling is carried out using the Knowledge Discovery in Database (KDD) methodology with the stages of dividing the dataset with a 50:50 percentage share into test and train data. The modeling uses hyperparameter tuning values, namely n_estimators = 1000, max_depth = 1, x_colsample_bytree = 0.9894, x_gamma = 0.9989, x_min_child = 1.0, x_reg_lamda = 0.2381, and x_subsample = 0.7063 with best loss or RMSE 451.4151. The values of Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) when making the model were 6.61374% and 3.95485%. Meanwhile, when testing the model, the RMSE is 0.23577% and MAPE is 0.11643%.
Stability analysis for yellow virus disease mathematical model of red chili plants
Authors: Amelia R , Anggriani N , Istifadah N , Supriatna A K
Published: January 2021

One of the main obstacles in the cultivation of red chili plants (Capsicum annuum) is the yellow virus disease caused by the Gemini virus. The virus is transmitted through insect vectors which can be controlled using insect pathogenic fungi (Verticillium lecanii). To understand the dynamics of the spread of the yellow virus in Capsicum annuum (C. annuum), we have formulated and analyzed a mathematical model of plant disease. From this model, the value of the Basic Reproduction Number (ℜ0) is presented, which is an essential quantity in an epidemiological model. The obtaining results indicate that when the value of ℜ0 is greater than one, the endemic equilibrium point is asymptomatically stable. However, if the value of ℜ0 is smaller than one, then the endemic equilibrium point is unstable. Also, we provide numerical simulations to illustrate the results.
Quadratic embedding constants of squid graph and kite graph
Authors: Purwaningsih M , Sugeng K A
Published: January 2021

The connected graphG= (V,E) is classified as a Quadratic Embedding (QE) class based on the distance matrixDwhich is conditionally definite negative and if the quadratic embedding constant (QEC) of the graphGis non-positive. In this study, QEC be calculated for Squid Graph containingC3,C4,C5, and kite graph containingC4. All of these graphs are included in the QE class, withQEC= 0 for squid graphs and kite graphs containingC4,QEC(Sq(3,m)) < 0 for squid graphs containingC3, and also for squid graphs containingC5.
Some characterizatsion of coprime graph of dihedral group D
2n
Authors: Syarifudin A G , Nurhabibah  , Malik D P , Wardhana I G A W
Published: January 2021

The Coprime graph of group G denoted Γ
G
is a graph with vertices is an element of G, and two distinct vertices are adjacent when its order relative prime. In 2020, Gazir et al. give some characterizations of Γ
D

2n
for n a prime power. The method that uses in this paper is deductive proof by taking some example of a coprime graph of D
2n
, then generalized the characterization of example. This paper gives some characteristics of the coprime graph of a dihedral group for more general cases. One of the result, Γ
D

2n
is a multipartite graph with girth 3, radius 1, and diameter 2.
On Ramsey (Cn, H)-minimal graphs
Authors: Nabila M , Baskoro E T
Published: January 2021

Let F, G and H be given simple graphs. The notation F → (G, H) means that for any red-blue coloring of all edges on F there is either a red copy of G or a blue copy of H as a subgraph of F. A graph F is called as a Ramsey (G, H)-minimal if it satisfies the following two conditions: (i) F → (G, H), and (ii) F − e ↛ (G, H) for any e ∈ F . The set of all Ramsey (G, H)-minimal graphs is denoted by R(G, H). In this paper, we study on the graphs in R(G, H) if G is a cycle Cn
and H is a path P
3. In particular, we construct some classes of such Ramsey minimal graphs.
Calculation of call option using trinomial tree method and black-scholes method case study of Microsoft Corporation
Authors: Lilyana D , Subartini B , Riaman  , Supriatna A K
Published: January 2021

Options are one of the most commonly known financial instrument used in financial market. Options are expected to minimize risk or even increase profits in stock trading. Therefore, it is important for options traders to take into account the contract price of options. This study discusses the determination of call option prices using the Trinomial Tree method and the Black-Scholes method with the data of Microsoft Corporation’s stock price and strike price. From the result of the calculations, a conclusion will be drawn from the comparison of the use of the two methods. In conclusion, the call option price using the trinomial tree method is close to the call option price using the Black-Scholes method. Therefore, the Trinomial tree method and the Black-Scholes method is worth using for the base calculation of option pricing.
Comparison of quadratic investment portfolio on five stocks of mining companies with risk free assets and without risk free assets
Authors: Pandiangan N. , Sukono  , Hasbullah E S
Published: January 2021

All types of investment have different risks. One way to avoid risk is to diversify the capital fund into several investment assets. The problem is determining the optimal differential weight for each asset. The purpose of this study is to determine the weight of the investment portfolio with risk free assets and without risk free assets. The method used in this study is a quadratic investment portfolio model. The optimization is done by using the Lagrangian Multiplier method. The assets analyzed used several mining stocks and deposits with an interest rate according to the Indonesian Bank rate. The expected results from this study are to obtain the optimal weight allocated to each asset in ordering an investment portfolio. Based on the results of the optimization, it can be used as a consideration for investors in making investments.
Premium estimation in the fire insurance through semiparametric bootstrap
Authors: Adnan W F , Pasaribu U S , Husniah H.
Published: January 2021

Along with the development of information, science and technology, there is a quite popular developing resampling method, namely bootstrapping. Bootstrap estimates asymptotically against its original value (observation). Thus, the greater bootstrap replication, the resample distribution will be normally distributed. It indicates that the bootstrap estimator gives better results. Based on the goodness-of-fit test by using Kolmogorov-Smirnov test, the severity on fire insurance data follow Weibull 2 parameter distribution. A case study is conducted on reinsurance company’s data for shopping centre’s fire. It is a big data. Since it is a reinsurance company’s data, the data completeness may be inadequate. It causes the severity claim to be processed using semiparametric bootstrap.
Forecasting the tuberculosis morbidity rate in Indonesia using temporal convolutional neural network and exponential smoothing
Authors: Kusuma A A A W , Mardiyati S , Lestari D
Published: January 2021

Tuberculosis (TB) morbidity rate in Indonesia shows the number of population in Indonesia who suffer from TB. The TB morbidity rate can be used by insurance companies to predict a person’s risk of TB so that insurance companies can determine the premiums that will be charged to insurance applicants based on the risks. Thus, the ability to estimate the TB morbidity rate accurately is essential for insurance companies to be able to determine the right premium amount while remaining competitive. This study compared two models that can be used to predict TB morbidity rate in Indonesia. The model was built using the temporal convolutional neural network (TCNN) and exponential smoothing methods. The data analyzed in this study are data obtained from the official website of the Ministry of Health of the Republic of Indonesia. Before the model was built, the data used in this study were compiled into training and validation datasets. The model is built using a training dataset and validated using the validation dataset. The results of the model’s validation are then evaluated and compared based on the value of the mean squared error (MSE). The result of this study shows that the TCNN model provides lower MSE compared to exponential smoothing.
Analysis of Hypothyroidism Development in Post-Radiotherapy Nasopharyngeal Cancer Patients using Survival Trees
Authors: George P M A , Abdullah S , Rachman A
Published: January 2021

Radiotherapy is one of the treatments for nasopharyngeal cancer (NPC). However, this treatment might produce an unfavorable effect on the thyroid gland, which eventually results in less production of thyroid hormone. This is condition is known as hypothyroidism. The development of hypothyroidism in each patient with post-radiative NPC differs according to several factors. This study aims to analyze the rate of development of hypothyroidism in post-radiated NPC patients. This aim is achieved by identifying subgroups of patients with different hazard rates of developing hypothyroidism, and further identify factors explaining hypothyroidism in each subgroup. Data on ninety-seven NPC post-radiation patients taken from one of the hospitals in Jakarta were analyzed. Survival tree with the relative risk tree algorithm was proposed to analyze the data. We identified three subgroups of patients with relatively slow, medium, and fast developing of hypothyroidism. For the slow subgroup, 26% of the patients developed hypothyroidism at 150+ weeks post-radiation, while it only took less than 30 weeks for those in fast-growing subgroup; and 70 until 130 weeks for the medium subgroup. We also found that sweat production and Zulewski’s total score were the important factors in explaining the development rate of hypothyroidism.
Identification of risk factors for impulse-control disorder symptoms in patients with Parkinson’s disease
Authors: Setianingsih D A , Abdullah S
Published: January 2021

Parkinson’s disease (PD) is one of the motoric neurodegenerative disorders that has the fastest-growing prevalence, disability, and death rate compared to other neurological disorders. Globally, from 1990 to 2015, the number of individuals with PD increased by 118%, up to around 6.2 million. There are several motor symptoms and non-motor symptoms that occur in Parkinson’s disease. One of the non-motor symptoms that occur is Impulse-Control Disorder (ICD). In PD, there are 4 main symptoms of ICD that often occur such as pathological gambling, binge-eating, compulsive buying, and compulsive sexual behaviour. ICD is often discovered when the treatment of PD begins, so this research focused on the incidence of ICD as a result of the treatment of PD. The purpose of this study is to identify risk factors for the type and number of ICD symptoms that occur in patients with PD. Both binary and multiclass classification tree methods were implemented to identify risk factors associated with the incidence of ICD for PD patients. Imbalance data problems that arose were handled with Synthetic Minority Over-sampling Technique (SMOTE). The results obtained show that the STAI-Trait total score is a risk factor that always appears for each type of, and the number of type of, ICD symptoms that appear. Moreover, risk factors that only appear in several symptoms are the length of education taken, STAI-State total score, age, duration of PD, SCOPA-AUT total score, MOCA total score, and MDS-UPDRS 3 total score. While, risk factors that only appear for a particular symptom are family history of PD, DAT binding ratio, and dopamine agonist treatment.
The approximation of GSTAR model for discrete cases through INAR model
Authors: Huda N M , Mukhaiyar U , Pasaribu U S
Published: January 2021

Modelling non-negative discrete valued for time series analysis was introduced by previous researchers, that is Integer-Valued Autoregressive (INAR) model. The model involves both the parameter index and state space are discrete. Various phenomena within the scope of discrete cases are not only affected by previous discrete observations, but also affected by the discrete observations at surrounding locations in previous time. As a result, this model involves two parameter indices namely time and space, and also state space which are discrete. In continuous cases, a model has been introduced to overcome this problem, namely Generalized Space Time Autoregressive (GSTAR) model (discrete parameter index and continuous state space). Using this model to solve the discrete case produces a continuous forecast value, so it needs a discretization process. In the time series model for discrete cases, thinning operators have been introduced as a substitute for discretization in a continuous time series. The thinning operator paradigm in the discrete time series will be developed in the space-time model proposed in this paper. This paper will also introduce a new model, namely a space-time model for cases related to discrete cases. This means that the index of time and location parameters, as well as the state space used is a discrete state space. The properties that apply to the model are adopted from the INAR model and the GSTAR model for continuous cases. The main focus of this paper is the development of thinning operators from time series to space-time models. This paper also provides a modeling procedure using the GSTAR model for discrete cases. The result of this paper is the formation of a GSTAR model with a discrete state space.
Influence of biomodified mineral fertilizers on sawing quality of spring barley
Authors: Adaev N L , Krylov V A , Zanilov A Kh , Amaeva A G , Adaev I N
Published: January 2021

Nowadays, the ability to demonstrate the achievement of Russian spring barley selection is significantly limited. The reason for this is the poor use on the fields of agricultural enterprises of the possibility of increasing productivity by improving sowing qualities.
Comparative analysis of species of the genus Rosa L. on the territory of the Eastern European Plain
Authors: Ryabinina Z N , Lyavdanskaya O A , Bastaeva G T , Lebedev S V , Kalyakina R G , Ryabuhina M V
Published: January 2021

The methods of gel electrophoresis with some modification have been developed on the types of rose hips. Identification of a species, as well as determining the degree of its intraspecific polymorphism, includes analysis of individual seeds taken from a random sample of different populations. For identification and analysis of the purity of the composition of the seeds of cultivars, an analysis of at least 100–150 seeds of each cultivar is recommended. Spectra were recorded using a special digital (large-scale) scale, which allows fixing the position (“addresses”) of individual polypeptide components at positions from 1 to 122. Components of low intensity were taken for 1 point, and strong ones (bright) for 2 points. The high sensitivity of the polyacrylamide gel electrophoresis (PAGE) method in the presence of sodium dodecyl sulfate (DS-Na, SDS) and 2-mercaptoethanol to genetic differences at the level of small taxa is clearly manifested in rosehip species. The research results allow us to clarify the taxonomy of the genus Rosa.
Changing of the composition of the rumen microflora to improve the efficiency of feed use by ruminants
Authors: Duskaev G K , Nurzhanov B S , Rysaev A F , Rahmatulin Sh G
Published: January 2021

Ruminant animals use their symbiotic microorganisms in the rumen to hydrolyze plant fibers and generate energy and other nutrients, while the eukaryotic community (fungi) makes up about half of the total microbial biomass and plays a critical role in the effectiveness of use of lignocellulosic particles of feed components. The aim of the study was to develop a way to increase the efficiency of feed use by ruminants through the introduction of a composition of promising substances into the diet. The assessment of biodiversity included the following: sampling, outflow, purification, measurement of DNA concentrations, PCR, validation and normalization of libraries, followed by sequencing on the platform of high-performance sequencer MiSeq Illumina (USA). Introduction of new substances in the diet of cattle contributes to a change in the eukaryotic composition of the rumen microflora towards an increase in Ascomycota and Neocallimastigomycota phylums (when used together with Quercus cortex extract), which have cellulose and ligninolytic properties, more active development of Chytridiomycota (separate use of substances).
Technology for detecting highly productive animals based on elemental status assessment
Authors: Kharlamov A V , Frolov A N , Zavyalov O A
Published: January 2021

The studies were conducted on bull-calves of the Kalmyk breed (n = 100), age 12 months, live weight 326.4 ± 6.4 kg. In the course of the research, we performed a sampling of animal biosubstrates. The article studies a single nucleotide polymorphism of the growth hormone gene (rs135322669). The elemental composition of biosubstrates was determined by 25 indicators, by atomic emission and mass spectrometry (AES-ICP and MS-ICP). It was found that the frequency of occurrence of CC alleles in the sample was 62.0 %, CG – 26.0 and GG – 12.0 %, χ2Эмп=39.924,2 test – 5.99. Evaluation of the elemental status of calf bull revealed significant differences depending on the polymorphism in the bovine growth hormone gene. In bulls with the CC genotype, the exchange pool Ca, K, Na, Co, Cr, Cu, J, Se, B, Si, Li, V was significantly higher compared to the CG genotype; and Ca, K, Na, J, Se, B, Li in comparison with the GG genotype. CC genotypes to GG were characterized by the accumulation of toxic elements: Al, Pb, Hg, Cd. Consequently, under the same ecological conditions of breeding in calf bull with the CC genotype, the detoxification mechanisms are higher, which is reflected in the reduced concentration of toxic elements in the wool. A technology for identifying highly productive animals is proposed based on the selection of bulls by the level of toxic elements in wool, calculated on the basis of the sum of moles: Al, Cd, Hg, Pb, Sn, Sr at 8 months of age, which allows increasing productivity by 9.4-15.6%. It was concluded that there is a need to continue the research with the obligatory safety assessment of the toxic elements of the resulting meat products.
Assessment of the population structure of horses of the Priobskaya breed based on modern technologies
Authors: Zaitcev A M , Gavrilicheva I S , Blohina N V , Khrabrova L A , Kokorina N V
Published: January 2021

Priobskaya horse belongs to the group of northern forest breed and is located in Khanty-Mansi Autonomous Region along Ob River and its tributaries. Among other local horse breeds of Siberia this breed stands out for its endurance and resistance to mosquitoes and other insects. The aim of our work was to study the features of the population structure of Priobskaya horses by 17 distinctive markers: VHL20, HTG4, AHT4, HMS7, HTG6, AHT5, HMS6, ASB23, ASB2, HTG10, HTG7, HMS3, HMS2, ASB17, LEX3, HMS1 and CA425. The results of biotechnological DNA typing of 25 Priobskaya horses by STR loci show that gene pool of the studied population is represented by 121 alleles, typical of local horse breeds. Horses of this breed had a number of rare alleles, including unique variant HMS1R, which was not found in horses of European origin (Van de Goor et al., 2010). The breed had fairly high rates of genetic diversity, the mean number of alleles per loci (MNA) reached 7.12, the effective number of alleles (Ae) – 4.16. The analysis demonstrated good compliance between the observed (Ho=0.741) and the expected (He=0.731) heterozygosity level and the absence of population inbreeding (Fis=-0.017). Analysis of the phylogenetic relations between local horse breeds showed that Priobskaya breed has the highest coefficient of genetic similarity with Tuvinskaya (0.845) and Narymskaya (0.844) horses. Cluster analysis confirmed genetic uniqueness of Priobskaya.
The effect of the new probiotic feed additive rhodofen on blood indicators of gobies during fattening
Authors: Fenchenko N G , Kilmetova I R , Khairullina N I , Sabitov M T , Shamsutdinov D Kh , Aminova A L , Shagaliev F M , Farkhutdinova A R
Published: January 2021

This article is devoted to the study of the effect of the new probiotic feed additive rhodofen, containing live spore-forming microorganisms of the genus Bacillus – Bacillus subtilis and Bacillus licheniformis, on the morphological and biochemical blood parameters of Hereford bulls fed. The introduction of a probiotic feed additive rhodofen into the diet at a dose of 1.5 kg per ton of feed does not lead to pathological and inflammatory processes, and contributes to a more intense metabolism in the body.
Increasing the efficiency of beef production by means of correcting cicatricial digestion with a mineral complex and plant extract
Authors: Makaeva A M , Atlanderova κ N , Sizova E A , Duskaev G K
Published: January 2021

The study presents the results of evaluating the effect of oak bark extract (OBE) and FeCo alloy mineral complex (MC) on digestion processes in the rumen of cattle, in particular, digestibility, hydrogen index and microbiome. The use of FeCo alloy mineral complex with OBE leads to an increase in digestibility of dry matter of the feed by 12.0 % as compared to the control. Changes in the hydrogen ions concentration were in the range of 7.0–8.10 pH. It was revealed during the experiment that both individual and joint introduction of OBE and FeCo mineral complex affects quantitative content of ciliates and bacteria. 6 hours after feeding, the number of ciliates increased with introduction of OBE by 20.4 % relative to the control and protozoa mass with the addition of FeCo mineral complex increased by 111 % (p≤0.01). The data obtained when introducing combination of OBE and FeCo alloy mineral complex indicate an increase in ruminal digestion through the synergistic effect of the mineral complex and FeCo alloy. The studied substances can be used in the industrial production of animal feed.
The effect of silicon-containing substances on the digestibility of feed and energy exchange in the body of poultry
Authors: Mustafina A S , Rakhmatullin S G
Published: January 2021

The article discusses results of studying effects of various doses of ultrafine particles of silicon dioxide (SiO2) on the body of broiler chickens, the dynamics of their live weight, digestibility of nutrients in their diet and the transformation of energy and protein of the feed into the body of an experimental bird. It is established that the use of ultrafine silicon in feeding broilers will increase live weight of the experimental poultry by 3.3–3.5 %, reduce feed intake by 0.7–2.1 %, increase the digestibility of dry matter of growth compound feed by 0.8–1.2 %, raw fat – by 0.2–1.0 %, crude protein – by 0.2–0.5 %, and also increase the net growth energy in MJ per head by 3.5–3.9 %, as a percentage of gross energy – by 8.7–14.3 %, while reducing feed energy loss by 4.0 % and 2.4 %. Therefore, our data reflect the productive effect of highly dispersed silicon oxide on poultry.
Influence of technological manipulations on the parameters of equine semen quality
Authors: Naumenkova V A , Atroshchenko M M , Shirokova O V
Published: January 2021

The aim of the work was to determine the influence of traditional technological manipulation (vaccination of stallions) performed when housing animals, on the quality indicators of spermatozoa. As a result of the experiment, it was discovered that vaccination did not affect the potency of stallions. The time and the number of jumps on the mare were the same before and after vaccination. There were no changes in the number of spermatozoas in the ejaculate in the first and subsequent weeks after vaccination. The study of sperm indicators showed a decrease in mobility (P>0.95) and survival (P>0.99) of freshly obtained and cooled sperm. Control of frozen-thawed sperm showed an even more dramatic decrease in the quality of sperm after vaccination. So in the first two weeks after vaccination, sperm motility after thawing fell by an average of 40 % (P>0.99), survival – by 44–49 % (P>0.99). The number of whole membranes decreased (unreliably) only by the end of the second week after vaccination within 15 %. Changes in the morphological composition of germ cells were observed in the second half of observations as result of influence on spermatogenesis processes. An identical picture was observed after revaccination, carried out 4 months later. A very characteristic drop in sperm motility and survival occurred in the first two weeks after vaccination. By the end of the third week, these indicators began to recover, but before the end of observations (day 55), recovery occurred in the range of 80–92 %, which is important to consider when conducting cryopreservation of sperm.
Change of hematological indices from acclimatization period of cattle of milk direction
Authors: Shishkin V V , Tatarenko I Yu , Shulzhenko E A , Shishkina G Yu
Published: January 2021

The article presents the results of a study of the leukocyte composition dependence of the blood of cows of red-motley breed on their ability to acclimatize. Getting into new climatic conditions, animals undergo profound physiological changes. Acclimatization is one of the stress factors for cows. Determination of the presence of stress in cattle can be determined by establishing the dependence of the leukocyte composition of the blood of cows on their ability to adapt. On this basis, it is possible to carry out productive work to reduce the impact of stress on the animal’s body. In the process of research, hematological parameters were studied in dynamics in two groups of animals in the joint-stock company “Luch” in the Ivanovo district of the Amur region. The control group consisted of local cows of the red-motley breed, which are already adapted to the living conditions. An experimental group is a livestock imported from the Krasnoyarsk Territory. The change in blood leukogram indicators from the degree of acclimatization of cattle of the Red-motley breed was reliably established. The obtained research results confirm the possibility of analyzing the degree of adaptation of animals using a comparative analysis of leukograms of imported and local cattle. The results can be the basis for the development of methods for determining the degree of acclimatization and stress in animals. The technique is necessary for research aimed at developing ways and tools to reduce the effects of stress and combat its negative impact on the animal’s body. Farm specialists, in the presence of a control group not subject to stress, carried out the study under production conditions.