Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Lactobacillus casei subsp. casei R-68 Isolated from Dadih on the Procarcinogenic Enzyme Activity and Fecal Microflora Count of Rats Challenged with Pathogenic Bacteria

The human digestive tract is a complex ecosystem that may contain bacteria, yeast, and other microflora, which have harmful and beneficial effects on the host. Species of Lactobacillus and Bifidobacterium are most commonly used as probiotics. Lactobacillus casei subsp. casei R-68 (LCR-68) isolated from dadih, traditional fermented buffalo milk from West Sumatera has the potential to be used as probiotic. The purposes of the present study were to evaluate the ability of strain LCR68 to inhibit the growth of the pathogenic bacteria Listeria monocytogenes FNCC-0156 and Escherichia coli FNCC-19 and reduce the activity of fecal mutagen enzymes in Wistar rats. The in vivo test used 25 male Wistar rats with an average weight of 174 - 176 g. This study consisted of five groups of treatment with five rats of each group. The results show a significant increase in the growth in all groups, although a significantly lower weight gain was observed in rats challenged with Listeria monocytogenes and fed fermented milk LCR-68. The counts of aerobic and anaerobic microbes were the same in all groups. Significantly higher counts of lactic acid bacteria were determined after the application of fermented milk LCR68. Significantly lower counts of Escherichia coli were also observed after the application of fermented milk LCR68. The presence of LCR-68 in fermented milk reduced the activity of β-glucuronidase and β-glucosidase significantly in the feces of Wistar rats. Therefore, the strain R-68 as a probiotic is expected to be able to prevent the formation of procarcinogenic compounds into carcinogens that cause cancer in the digestive tract.
A Comparison of Clinical and Radiological Parameters in the Evaluation of Molar Furcation Involvement in Periodontitis

Objective The aim of this study was to compare clinical, intra-surgical, 2D (panoramic) and 3D (CBCT)-based parameters in assessing molar furcation involvement (FI). Materials and Methods Six patients with generalized periodontitis Stage II to IV, Grade B and C who were scheduled for the periodontal flap surgical treatment were recruited in the study. In total, 38 molar teeth with 93 furcation sites were analysed. All subjects had comprehensive periodontal examination, which included an assessment of molar FI using Naber’s probe according to modified Glickman’s classification. Periodontal surgery was performed in patients with at least one maxillary molar with probing depth of ≥6 mm. This probing demonstrated lower grade of FI compared with intra-surgical findings. Results Periodontal probing, intra-surgical measurement and measurements based on CBCT significantly correlated with each other regarding the assessment of FI, with r values ranging between 0.81 to 1.00 (p<0.01). The correlation of panoramic radiograph with periodontal probing is 0.49, with CBCT 0.39 and with intra-surgical measurements 0.36. The results showed an excellent agreement and higher accuracy between intra-surgical measurements and CBCT (0.96), in contrast to clinical examination and panoramic radiography- 0.87 and 0.63 respectively. Different clinical and radiological modalities showed a correlation among each other. They are accurate and have their own benefits, which makes (renders) them useful in establishing periodontal diagnosis and treatment planning. Conclusion However, CBCT offers significant advantages including excellent agreement and higher accuracy and can be used as justified as excellent diagnostic tool in detecting and locating FI to provide a more reliable diagnosis and basis for treatment decisions.
Short-term solar PV forecasting using computer vision: The search for optimal CNN architectures for incorporating sky images and PV generation history

Cloud movement makes short-term forecasting of solar photovoltaic (PV) panel output challenging. A better PV forecast can realize value for both grid operators and commercial or industrial customers with solar assets. In this study, we build convolutional neural network (CNN) based models to forecast power output from PV panels 15 min into the future. Model inputs are the PV power output history and ground-based sky images for the past 15 min. The key challenge is ensuring that due importance is given to each type of input. We systematically explore 28 methods of “fusing” these heterogeneous inputs in our CNN. These methods of fusion (MoF) belong to 4 families. We also systematically explore the many hyperparameters related to model training and tuning. Limited resources preclude an exhaustive search. We apply a three-stage “funnel” approach instead, wherein we narrow our search to the most promising one of these 28 MoF. We find that a two-step autoregression-CNN MoF has the best performance followed closely by a “mix-in” MoF that performs feature expansion and reduction to give appropriate importance to the two types of inputs. The two-step autoregression-CNN model has a forecast skill (FS) of 17.1% relative to smart persistence on the test set comprising 20 complete days (9 sunny, FS = 22%; 11 cloudy, FS = 16.9%). This optimization results in the improvement of FS from 14.1% for a previously published nonoptimized “baseline” model, a CNN wherein the PV history was simply concatenated to the end of the image-sourced vector obtained after convolution, pooling, and flattening operations.Cloud movement makes short-term forecasting of solar photovoltaic (PV) panel output challenging. A better PV forecast can realize value for both grid operators and commercial or industrial customers with solar assets. In this study, we build convolutional neural network (CNN) based models to forecast power output from PV panels 15 min into the future. Model inputs are the PV power output history and ground-based sky images for the past 15 min. The key challenge is ensuring that due importance is given to each type of input. We systematically explore 28 methods of “fusing” these heterogeneous inputs in our CNN. These methods of fusion (MoF) belong to 4 families. We also systematically explore the many hyperparameters related to model training and tuning. Limited resources preclude an exhaustive search. We apply a three-stage “funnel” approach instead, wherein we narrow our search to the most promising one of.
Energy efficiency and company performance in Japanese listed companies

This research empirically investigates the relationship between energy efficiency and company performance for a pooled sample of 177 listed companies in Japan over 2005-2014. We find that energy efficiency plays a significant role in company performance in Japan, thereby debunking the energy efficiency paradox. Our research further indicates that this energy efficiency not only affects the market-based performance (Tobin's Q), but it also significantly impacts the accounting-book performance (return on assets). The findings present significant contributions to both the academic body of knowledge and the industry. The findings can also provide a basis for the Japanese Government to encourage companies to enact more energy efficient practices.
The Role Of Self Efficacy And Relicience On The Job Insecurity Of Contract Employees

Self-efficacy and employee resilience are factors that can affect job insecurity. This study aims to empirically examine the role of self-efficacy and resilience on job insecurity of contract employees at PT. Mega Andalan Kalasan. The population in this study is contract employees in ten units at PT. Mega Andalan Kalasan, who are still actively working, and have worked at least three months. The sample in this study consist of 56 contract employees in the EOP unit of PT. Mega Andalan Kalasan. The sampling technique used is quota sampling, while the data collection method is the selfefficacy scale, resilience scale, and job insecurity scale. Multiple linear regression analysis shows that self-efficacy and resilience have a very significant effect on the job insecurity of contract employees (R = 0,600, p = 0,000). There is a very significant negative relationship between self-efficacy and job insecurity among contract employees, with a correlation coefficient of rxy = -0,549, p = 0,000 (p <0.01). Similarly, there is also a very significant negative relationship between resilience and job insecurity among contract employees, with a correlation coefficient of rxy = -0,476, p = 0,000 (p <0.01). Selfefficacy and resilience contribute 36% to job insecurity, while the remaining 64% are influenced by other factors outside the scope of this study.
Relationship between STAT6 Gene Polymorphism and Bronchial Asthma in Li Nationality People in Hainan

Objective To discuss the relationship between STAT6 gene polymorphism and bronchial asthma of Li nationality in Hainan.Methods The polymerase chain reaction-restriction fragment length polymorphism(PCR-RLFP) was used to detect the STAT6 gene G2964A polymorphism of 115 healthy adults and 108 adult asthma patients of Li nationality in Hainan.The genotypes and allele frequencies were between the two groups compared.Results The GA genotype was the most common for the people of Li nationality in Hainan,followed by AA type and GG type.A-type allele was the most common,followed by G-type.No significant difference was found in genotype frequency and allele frequency between the two groups(P0.05). The levels of total serum IgE of asthma patients with GA,AA,and GG genotypes were significant higher respectively than those of control subjects with the same corresponding genotypes(P0.01). But there was no significant difference in level of serum total IgE among GG,GA and AA genotypes in both the asthma group and the control group(P0.05). Conclusion The STAT6 gene G2964A polymorphism is not significantly correlated with asthma susceptibility and serum total IgE levels for people of Li nationality,which may not be an independent risk factor for asthma.
Physical Processing and Emission Characteristics of Firelogs from Cotton Ginning Byproducts

Cotton burr with stems (CBS), a byproduct from cotton ginning operations was evaluated for its suitability in firelogs. Firelog burn quality was examined by varying the CBS to paraffin wax ratio, and firelog processing conditions. The firelogs were burned in a wood stove to quantify the burn quality, burn time, product durability, and gaseous emissions. Firelog composition had no effect on the burn temperatures. Carbon monoxide (CO), ammonium (NH4), hydrogen (H2), and nitrous oxide (NO) gases were not detected in the gaseous emissions. Air emission samples from combustion showed the presence of n-alkanes, n-alkenes, oxygenated volatile organic compounds, polycyclic aromatic hydrocarbons (PAH), halogenated alkane, cyclic terpenes, benzene derivatives and naphthalene. Overall this study showed the potential of CBS as an alternative material for manufacturing firelogs.
Dental caries, hygiene, fluorosis and oral health knowledge of primary school teachers of Riyadh, Saudi Arabia

The objectives of this study were to determine the status of caries, oral hygiene condition and fluorosis of primary school teachers of Riyadh urban area and to assess some basic knowledge about oral diseases and habits of these subjects. Two hundred ninety seven male school teachers were selected randomly from 16 public schools, using stratified cluster random sampling. High caries experience and fluorosis level were observed when compared with the general normal population of Riyadh region. Five percent of the teachers did not clean their teeth. One-third of the teachers showed poor knowledge about caries and gum diseases. Even though very few teachers were involved in giving lectures about preventive measures and oral diseases, nevertheless more than ninety percent of them agreed that these types of lectures were beneficial to the students.
Enhancing Distribution System Resilience With Proactive Islanding and RCS-Based Fast Fault Isolation and Service Restoration

The resilience of power systems against extreme events has become a growing concern in recent years. In view of the fact that the resilience of a distribution system depends on its system function throughout the entire multi-stage recovery process after extreme events, and to comprehensively improve the abilities of distribution systems in resisting and rapidly recovering from extreme events, it is necessary to consider this multi-stage recovery process. In this paper, a novel resilience enhancement method is proposed, where proactive islanding and RCS (remote-controlled switch)-based fast fault isolation and service restoration are comprehensively considered to improve the abilities of distribution systems in resisting and rapidly recovering from extreme events. The multi-stage recovery process is modeled in detail, including the topological and operational constraints of each stage in the multi-stage recovery process, as well as the coupling relationship among the stages. The model is formulated as a mixed-integer linear programming problem and applies to scenarios where the network topology varies. Resilience metrics based on the proposed method are introduced to evaluate the resilience level. Case studies on the IEEE 33-bus system and the real-world 94-bus system show that the proposed method is effective at resilience enhancement.
Level Crossing Rate and Average Fade Duration in $\mathcal{F}$ Composite Fading Channels

In this letter, we derive exact closed-form expressions for the level crossing rate (LCR) and average fade duration (AFD) of the signal envelope in $\mathcal {F}$ composite fading channels. Using the novel expressions, we then investigate the behavior of the LCR and AFD for different multipath fading and shadowing conditions. It is shown that multipath fading has a more significant effect on the LCR at lower fade levels while shadowing tends to have a discernible impact on higher threshold levels. In contrast, shadowing has a more noticeable effect on the AFD compared to multipath fading at both lower and higher levels. Approximate expressions for the LCR and AFD are also provided, and shown to be in good agreement with the exact LCR and AFD as they approach lower and higher threshold levels. The offered results are expected to be useful in the design of emerging systems such as device-to-device communications.
No Evidence That Frontal Optical Flow Affects Perceived Locomotor Speed and Locomotor Biomechanics When Running on a Treadmill

We investigated how the presentation and the manipulation of an optical flow while running on a treadmill affect perceived locomotor speed (Experiment 1) and gait parameters (Experiment 2). In Experiment 1, 12 healthy participants were instructed to run at an imposed speed and to focus on their sensorimotor sensations to be able to reproduce this running speed later. After a pause, they had to retrieve the reference locomotor speed by manipulating the treadmill speed while being presented with different optical flow conditions, namely no optical flow or a matching/slower/faster optical flow. In Experiment 2, 20 healthy participants ran at a previously self-selected constant speed while being presented with different optical flow conditions (see Experiment 1). The results did not show any effect of the presence and manipulation of the optical flow either on perceived locomotor speed or on the biomechanics of treadmill running. Specifically, the ability to retrieve the reference locomotor speed was similar for all optical flow conditions. Manipulating the speed of the optical flow did not affect the spatiotemporal gait parameters and also failed to affect the treadmill running accommodation process. Nevertheless, the virtual reality conditions affected the heart rate of the participants but without affecting perceived effort.
Expansion Planning Studies of Independent-Locally Operated Battery Energy Storage Systems (BESSs): A CVaR-Based Study

Nowadays, the high penetration of renewable energy resources, with variable and unpredictable nature, poses major challenges to operation and planning studies of power systems. Employing energy storage systems (ESSs) has been introduced as an effective solution to alleviate these challenges. Several studies have been presented in the literature to provide a framework for expansion planning studies of ESSs. However, they usually have two main drawbacks: i) ignoring the positive effect of independent-locally operated ESSs on the bulk power system preferences, ii) inability to model the charge/discharge schedule of independent-locally operated ESSs based on their investors’ acceptable risk level. This paper amends the abovementioned shortcomings by proposing a new bi-level framework for expansion studies of ESSs, where the long-term total cost of bulk power systems and the scheduling of independent-locally operated ESSs are modeled in the upper level (UL) and lower-level (LL) problems, respectively. Moreover, the proposed methodology is formulated based on benders dual decomposition technique to effectively reduce the computational effort. Finally, the proposed methodology is implemented on the modified IEEE 73-bus test system, and the results reveal the effectiveness of the proposed ESS planning framework.
Meta-analysis of Human Papillomavirus (HPV) Prevalence and Type Distribution in Cervical Lesions in Chinese Population

Objective To explore the overall prevalence and type distribution of human papillomavirus(HPV) in the cervical lesions in Chinese women.Methods Meta-analysis was conducted on studies published from Jan 1999 to Sep 2008 to evaluate synthetically the relationship between HPV infection and the lesions of Cervix.Results The overall HPV prevalence was 46.51%(5632/12110) in cervical lesion in Chinese women.HPV positive rate was higher in northern China than in southern (55.67% VS 42.06%,P0.01). The 5 commonest HPV types in China were HPV-16,HPV-18,HPV-58,HPV-52 and HPV-33.Except HPV-16,the distribution of other common types of HPV varied with regions.The rate of HPV infection was positively correlated with the degree of cervical lesions(r=0.815,P0.01). HPV-16 was the commonest type in all degrees of cervical lesions and its infection rate was positively correlated with the degree of cervical lesions(r=0.823,P0.01). Conclusion HPV infection rate and distribution vary in some extent in different regions and in various lesions of cervical tissue,mainly high-risk HPV-16,-58,-18.
Clinical Effectiveness of Acupotome and Manipulation in the Treatment of Knee Osteoarthritis and Its Effect on Plasma Metabolism of Oxygen Free Radicals

Objective: To observe the clinical effectiveness of acupotome and manipulation in the treatment of knee osteoarthritis and its effect on plasma metabolism of oxygen free radicals(OFR). Methods: 100 patients with knee osteoarthritis were randomly divided into 2 groups.Fifty patients in observation group were treated with acupotome and manipulation,and those in control group with Diclofenac sodium enteric-coated tablets.Results: In observation group,the curative rate was 64.0% and the total effective rate was 98.0%. In control group,the curative was 44.0% and the total effective rate was 86.0%. There was significant difference between two groups(P0.05). There was significant difference in the JOA score in the two groups before and after treatment(P0.01). There was significant difference in the pain of down stairs,the pain while walking and the function of total score between two groups.After treatment,the plasma SOD level was significantly increased,LPO and MDA levels were reduced as compared with those before treatment,and there was significant difference between two groups(P0.05). Conclusion: The acupotome and manipulation treatment can alleviate the clinical symptoms and signs,restore the balance of plasma OFR,inhibit the damage of OFR to cartilage cells and matrix.
Building 21st century business skills in high school business classrooms using digital games and simulations

Digital games and simulations are often seen as fun activities to reward students but their potential is much greater. This literature review examined how integrating digital games and simulations into secondary business curriculum can help students build the skills needed for the 21st century workplace in an environment that is conducive to how they learn best. The effects of digital games and simulations on student motivation are also examined as well as how to assess student learning while using these tools. The infonnation found came from peer-reviewed journals, books, and studies from the Web. Digital games and simulations have proven to have a positive effect when used in secondary classrooms. More research needs to be compiled on how to implement them successfully in the classroom.
Cuffless Deep Learning-Based Blood Pressure Estimation for Smart Wristwatches

In this article, we propose a cuffless blood pressure (BP) estimation technique based on deep learning for smart wristwatches. Photoplethysmography (PPG) and electrocardiography (ECG) signals are first collected from the sensors installed at a smart wristwatch. Ground-truth systolic BP (SBP) and diastolic BP (DBP) measurements are then obtained by a reference device, a mercury sphygmomanometer. In order to estimate the SBP and DBP, we extract feature vectors and reconstruct them through a feature selection process. Next, we design a two-stage system of stacked deep neural network (DNN)-based SBP and DBP estimation models and compare our results with those obtained using estimation techniques in the previously reported algorithms such as the polynomial regression (PR), support vector machine (SVM), artificial neural network (ANN), and deep belief network (DBN)-DNN. In order to verify the proposed algorithm against the conventional algorithms, we quantitatively compare the results in terms of mean error (ME) with standard deviation, mean absolute error (MAE) with standard deviation, Pearson correlation, box plot, and Bland–Altman plot. For this, 110 subjects contributed to the database (DB), each of which is collected three times for 20 s. The quantitative errors turn out to be lower than that of the existing methods, which shows the superiority of our approach. To enhance the BP estimation performance for each individual user further, we devise the personal adaptation algorithm for the BP estimation algorithm that yields better BP estimates.
Sparse Direct Adaptive Equalization for Single-Carrier MIMO Underwater Acoustic Communications

The sparse direct adaptive equalization technique recently received many attentions for single-carrier underwater acoustic communications. By taking advantage of the sparse (nonuniform) structure of a direct adaptive equalizer (DAE), one obtains a sparse DAE with improved performance and/or reduced complexity compared with its nonsparse counterpart. In this article, the sparse DAE is revisited with two contributions made: First, a comprehensive comparison is made for existing sparse DAEs designed with the proportionate-updating (PU) or the zero-attracting (ZA) adaptive filtering principles. The comparison concludes that the PU-type DAE outperforms the ZA-type DAE in terms of complexity, performance, and operability, thus shall be favored in practical use. Moreover, it motivates the design of a sparse DAE, named the selective ZA improved proportionate normalized least mean squares DAE (SZA-IPNLMS-DAE), based on the combination of the PU and ZA principles. The SZA-IPNLMS-DAE outperforms existing sparse DAEs armed with only one sparsity-promoting mechanism; second, a partial tap update (PTU) scheme via hard thresholding is introduced to sparse DAEs for reducing their complexity without sacrificing performance. The resulting low-complexity and high-performance sparse PTU-DAE schemes are strong candidates for single-carrier UWA communications. Experimental results of multiple-input multiple-output UWA communications are presented to corroborate all above claims.