Miracle-dz/UniFAR-FTUs huggingface dataset:
Response of Cyanic and Acyanic Lettuce Cultivars to an Increased Proportion of Blue Light

Simple Summary Indoor crop cultivation systems such as vertical farms or plant factories necessitate artificial lighting. The composition of light quality (i.e., spectral composition) within these systems plays a key role in crop growth and development. Conflicting results on the effects of the light spectrum reported for different plant species and cultivars confirm the specificity of light requirements and the dependency on interacting factors. In this paper, we have therefore investigated how a certain light quality (light with a high share of blue) affects photosynthetic and morphological parameters in two contrasting lettuce cultivars (red and green leaves) with a similar leaf shape and phenotype. The results obtained suggest the occurrence of distinctive morpho-physiological adaptive strategies in green and red pigmented lettuce cultivars to adapt to the higher proportion of blue light environment. Abstract Indoor crop cultivation systems such as vertical farms or plant factories necessitate artificial lighting. Light spectral quality can affect plant growth and metabolism and, consequently, the amount of biomass produced and the value of the produce. Conflicting results on the effects of the light spectrum in different plant species and cultivars make it critical to implement a singular lighting solution. In this study we investigated the response of cyanic and acyanic lettuce cultivars to an increased proportion of blue light. For that, we selected a green and a red leaf lettuce cultivar (i.e., ‘Aquino’, CVg, and ‘Barlach’, CVr, respectively). The response of both cultivars to long-term blue-enriched light application compared to a white spectrum was analyzed. Plants were grown for 30 days in a growth chamber with optimal environmental conditions (temperature: 20 °C, relative humidity: 60%, ambient CO2, photon flux density (PFD) of 260 µmol m−2 s−1 over an 18 h photoperiod). At 15 days after sowing (DAS), white spectrum LEDs (WW) were compared to blue-enriched light (WB; λPeak = 423 nm) maintaining the same PFD of 260 µmol m−2 s−1. At 30 DAS, both lettuce cultivars adapted to the blue light variant, though the adaptive response was specific to the variety. The rosette weight, light use efficiency, and maximum operating efficiency of PSII photochemistry in the light, Fv/Fm’, were comparable between the two light treatments. A significant light quality effect was detected on stomatal density and conductance (20% and 17% increase under WB, respectively, in CVg) and on the modified anthocyanin reflectance index (mARI) (40% increase under WB, in CVr). Net photosynthesis response was generally stronger in CVg compared to CVr; e.g., net photosynthetic rate, Pn, at 1000 µmol m−2 s−1 PPFD increased from WW to WB by 23% in CVg, compared to 18% in CVr. The results obtained suggest the occurrence of distinct physiological adaptive strategies in green and red pigmented lettuce cultivars to adapt to the higher proportion of blue light environment.
The Validity and Reliability of the Physical Activity Questionnaires (PAQ-A) among Indonesian Adolescents during Online and Blended Learning Schooling

Research objectives. This study aimed to validate the use of the Physical Activity Questionnaire Adolescent (PAQ-A), a physical activity instrument widely used in a school setting, among Indonesian adolescents, particularly during blended learning or online schooling due to COVID-19 restrictions. Materials and methods. This study was a cross-sectional survey of 370 Indonesian adolescents (62.2% female, mean 15±2 years) participating in online and blended learning. Participants completed the Indonesian version of the PAQ-A online. Sixty-three (17%) participants completed the same questionnaire one week later (second survey) for the test-retest reliability, from which the intraclass correlation coefficients (ICC) were calculated. Internal consistency reliability was calculated in both surveys, while confirmatory factor analysis (CFA) was analyzed from the data in the first survey. Results. The Cronbach alpha of the PAQ-A for the first and second surveys was 0.78 and 0.82, thus indicating the acceptability of internal consistency reliability. The ICC for all PAQ-A items ranged from 0.40 to 0.81, indicating fair to excellent test and retest reliability. The root means square error of approximation was 0.033 suggesting acceptable construct validity of the instrument. Conclusions. In conclusion, sufficient evidence shows the validity and reliability of the PAQ-A to justify the use of the questionnaires for measuring physical activity levels in the Indonesian adolescents in the blended learning or online schooling setting.
Isolation of Chitinolytic Bacteria from European Sea Bass Gut Microbiota Fed Diets with Distinct Insect Meals

Simple Summary The ever-growing human population is increasingly demanding more fish. As a response, aquaculture has become the fastest growing industry in its sector. Alternatives to fish meal, an unsustainable commodity used as the main protein source for carnivorous species, are urgently needed in aquafeeds. Recently, in Europe, seven insect species have been approved as potential ingredients for animal feeds, including fish feed. However, chitin, one of the components of an insect’s exoskeleton, is indigestible for several economically valuable fish species, decreasing fish performance upon inclusion. This work aimed to isolate, from the European sea bass gastrointestinal tract, probiotic bacteria capable of producing chitinases to improve the use of diets containing high levels of insect meal. Based on the enhanced adaptability of gut microbial communities and the selective pressure of chitin-enriched diets on fish gut microbiota, bacteria were first isolated from the gastrointestinal tract of European sea bass fed chitin-enriched diets. Isolates were then comprehensively screened in vitro for important traits such as their ability to utilize chitin, gut-survival aptitude, and biosafety-related issues required to be considered eligible as probiotics by the European Food Safety Authority (EFSA). Abstract Insect meal (IM), recently authorized for use in aquafeeds, positions itself as a promising commodity for aquafeed inclusion. However, insects are also rich in chitin, a structural polysaccharide present in the exoskeleton, which is not digested by fish, resulting in lower fish performance. Through the application of a dietary pressure, this study aimed to modulate European sea bass gut microbiota towards the enrichment of chitinolytic bacteria to allow the isolation of novel probiotics capable of improving the use of IM-containing diets, overcoming chitin drawbacks. Five isoproteic (44%) and isolipidic (18%) diets were used: a fish meal (FM)-based diet (diet CTR), a chitin-supplemented diet (diet CHIT5), and three diets with either 25% of Hermetia illucens and Tenebrio molitor larvae meals (HM25 and TM25, respectively) or H. illucens exuviae meal (diet HEM25) as partial FM substitutes. After an 8-week feeding trial, the results showed a clear modulatory effect towards spore-forming bacteria by HM25 and HEM25 diets, with the latter being responsible for the majority of the chitinolytic fish isolates (FIs) obtained. Sequential evaluation of the FI hemolytic activity, antibiotic resistance, total chitinolytic activity, sporulation, and survival in gastrointestinal-like conditions identified FI645 and FI658 as the most promising chitinolytic probiotics for in vivo application.
Affinity estimation models of proteins for intelligent drug design based on pseudoconvolutions and nonlinear regressors

Purpose: The emergence of new viruses and, consequently, new diseases make the rapid and precise design of new drugs increasingly necessary. With the availability of large databases of proteins and affinity measures, it is possible to build scoring functions for predicting molecular affinity. These functions are fundamental to intelligent drug design. Objective: In this work, we propose a scoring function to predict affinity between two proteins. The method is based on extracting features by transfer learning on sequences represented on pseudo-convolutions. Method: The pseudo-convolutions organize the sequences into base neighborhood distributions. Each distribution is then represented by an image. Two proteins are then transformed into two images that are concatenated together, forming the third image. Through deep transfer learning, this resulting image is then represented by a vector of attributes, which have dimensionality reduced by Random Forest. Finally, the vector of attributes reduced is applied to a regression learning machine that returns the degree of affinity of the two proteins. Results: We used the Affinity Benchmark Version 2 database. 145 complexes were used for model training and 35 for testing. The results showed a performance equal to or better than the state-of-the-art methods of evaluating protein affinity, considering the correlation coefficients of Pearson, Spearman and Kendall. The best results were 0.66, 0.70, and 0.52. Conclusion: The proposed method can characterize protein sequences so that the binding affinity between two proteins can be estimated without simulating the three-dimensional structure of the complex.
Learning Temporal and Spatial Correlations Jointly: A Unified Framework for Wind Speed Prediction

Leveraging both temporal and spatial correlations to predict wind speed remains one of the most challenging and less studied areas of wind speed prediction. In this paper, the problem of predicting wind speeds for multiple sites is investigated by using the spatio-temporal correlation. We proposed a deep architecture termed predictive spatio-temporal network (PSTN), which is a unified framework integrating a convolutional neural network (CNN) and a long short-term memory (LSTM). Initially, the spatial features are extracted from the spatial wind speed matrices by the CNN at the bottom of the model. Then, the LSTM captures the temporal dependencies among the spatial features extracted from contiguous time points. Finally, the predicted wind speeds are given by the last state of the top layer of the LSTM, which are generated by using the spatial features and temporal dependencies. Though composed of two kinds of architectures, PSTN is trained with one loss function in an end-to-end manner, which can learn temporal and spatial correlations jointly. Experiments for short-term predictions are conducted on real-world data, whose results demonstrate that PSTN outperforms prior methods.
Training statistics teachers for Botswana senior schools: is it necessary?

The study sought teachers’ views on the need to train statistics teachers in Botswana. A purposive sample comprising 23 senior teachers and 30 ordinary teachers responded to an open-ended questionnaire soliciting their experiences about the teaching of statistics in schools. It was found that all teachers offering statistics had limited qualifications to teach statistics as they have been trained for mathematics teaching. The biggest challenges in statistical instructional practices were difficulties in solving questions and explaining concepts to students. The study findings suggest the necessity to train teachers so as to empower them with statistical pedagogical content knowledge and knowledge for teaching statistics.
A Student-Centered Approach for Assessing Sexuality Education in the Classroom

Abstract In the past decade, several states have introduced comprehensive sexuality education standards for public schools, but the impact is unknown because mechanisms to monitor adherence and improve quality have been lacking. In this study, we pilot-tested an approach for high school students to assess sexuality education standards mandated by the California Healthy Youth Act. We introduced a 15-minute online survey administered at the conclusion of sexuality education instruction. Results from thirteen Los Angeles high schools indicated that the approach was acceptable, feasible, and valid. It provided actionable data about which standards were being followed and whether the classroom environment was conducive to learning.
Performance evaluation of 2 × 2 MIMO-OFDM-based radio-over-fibre system using Alamouti coding and Hammerstein equaliser

Radio-over-fibre (RoF) systems consist of two subsystems including optical subsystem and wireless radio frequency subsystem. It is shown that by using multiple-input multiple-output (MIMO) and orthogonal frequency-division multiplexing (OFDM) systems, the RoF transmission can be improved in frequency-selective channels. In this study, two different configurations of MIMO–OFDM-based RoF systems are compared for the long-term evolution standard under different non-linearity levels, bandwidths, and fading channel conditions. Using the total degradations (TD) criterion, an appropriate quiescent point is determined to decrease the impact of non-linearity level, and hence the performances of different MIMO detection methods are compared. Bit error rate results demonstrate that by using Hammerstein type equaliser, the system performance is improved under different conditions including different fading channels, Doppler frequencies, bandwidths, and output back off levels. Results demonstrate that with an appropriate structure for MIMO–OFDM–RoF systems, a suitable quiescent point can be found for all scenarios by employing Alamouti coding and Hammerstein equaliser.
Constant current/voltage charging for the inductor–capacitor–inductor‐series compensated wireless power transfer systems using primary‐side electrical information

This study presents an investigation into the use of primary-side electrical information to achieve constant current/voltage (CC/CV) charging for the inductor-capacitor-inductor-series compensated wireless power transfer systems. It uses the relationship of the phase difference between the transmitter resonant current and compensation capacitor voltage to control the charging current and voltage. The cosine and sine values of phase difference are obtained by the quadrature transformation algorithm, and then the CC/CV charging is achieved by the proportional-integral-controlled phase shift H-bridge inverter. The simulation and experimental results verify the feasibility of the control method. The accuracy of CC charging (3 A) and CV charging (25.8 V) is 98.7 and 98.4%, respectively. The advantages of the proposed control method are that the wireless communication link between the transmitter and receiver is avoided and the CC/CV charging defined by the battery charging profile is realised.
Understanding the Impact of Deviant Peer Association on Risk for Stimulant/Amphetamine Use: The Moderating Role of Exposure to Violence

Prior research has indicated that deviant peer association is associated with increased risk for stimulant/amphetamine use. However, there remain gaps in our understanding of the context under which this relationship occurs. This study examined two forms of exposure to violence (direct victimization, witnessed violence) as moderators of the relationship between deviant peer association and stimulant/amphetamine use risk. All 11 waves of the Pathways to Desistance longitudinal data were used in analyses. Mixed effects logistic regression models were used to estimate relationships of interest while accounting for repeated measures nested within individual participants across time. Findings indicated that greater deviant peer association was associated with greater odds of stimulant/amphetamine use. Experiencing direct victimization significantly moderated this relationship, but in the opposite of the hypothesized direction, with individuals reporting direct victimization also reporting less reactivity to deviant peer association as it pertained to stimulant/amphetamine use. Witnessed violence did not moderate this relationship.
Ensemble learning for the partial label ranking problem

The partial label ranking problem is a general interpretation of the preference learning scenario known as the label ranking problem, the goal of which is to learn preference classifiers able to predict a complete ranking with ties over the finite set of labels of the class variable. In this paper, we use unsupervised discretization techniques (equal‐frequency and equal‐width binning) to heuristically select the threshold for the numerical features in the algorithms based on induction of decision trees (partial label ranking trees algorithm). Moreover, we adapt the most well‐known averaging (bootstrap aggregating and random forests) and boosting (adaptive boosting) ensemble methods to the partial label ranking problem, in order to improve the robustness of the built classifiers. We compare the proposed methods with the nearest neighbors‐based algorithm (instance based partial label ranking) over the standard benchmark datasets, showing that our versions of the ensemble methods are superior in terms of accuracy. Furthermore, they are affordable in terms of computational efficiency.
Effectiveness of Telerehabilitation on Hamstring Flexibility in Healthy Adults

Background. Telerehabilitation used as an exercise method has become increasingly common in recent years. Various methods have been used to increase hamstring flexibility, but more research is required on the optimal program. The study purpose was to investigate the effect of hamstring stretching exercises given as telerehabilitation and home exercise program on hamstring flexibility. Materials and methods. Sixty-eight healthy adults were randomly assigned to two groups, namely telerehabilitation and home exercise. Exercises were performed for 8 weeks (4 sessions/week) in both groups. Active and passive range of motion (ROM), sit and reach test (SRT), and International Physical Activity Questionnaire Short Form (IPAQ-SF) were conducted in the pre- and post-intervention and after a 6-month period. Results. At the end of 8 weeks, a significant improvement was observed in the SRT scores in both the telerehabilitation group (p = 0.001) and the home exercise group (p = 0.001). In addition, significant improvements were observed in the passive ROM measurements of both the telerehabilitation group (p = 0.005) and the home exercise group (p = 0.001). At the end of 8 weeks, the telerehabilitation group was found to be significantly superior to the home exercise group in the SRT results (p = 0.034). As for the long-term results, significant improvement was maintained in both SRT (p = 0.001) and passive ROM (p = 0.014) in the telerehabilitation group. Conclusions. Eight-week telerehabilitation and home exercise program was observed to have positive effects on passive and active ROM. The telerehabilitation method may prove to be more effective than the home exercise method in the long term.
CCL22-Polarized TAMs to M2a Macrophages in Cervical Cancer In Vitro Model

Macrophages are dynamic cells susceptible to the local microenvironment which includes tumor-associated macrophages (TAMs) in cancers. TAMs are a collection of heterogeneous macrophages, including M1 and M2 subtypes, shaped by various activation modes and labeled with various markers in different tumors. CCL22+-infiltrating cells are thought to be significantly associated with the prognosis of cervical cancer patients. Moreover, CCL22 is an established marker of M2a macrophages. Although the phenotypic identification of M1 and M2 macrophages is well established in mice and human macrophages cultured in a medium with fetal calf serum (FCS), fewer studies have focused on M2 subtypes. In addition, the question of whether CCL22 affects polarization of M2a macrophages remains unanswered. This study constructed a co-culture system to shape TAMs in vitro. We found that CCL22 was mainly secreted by TAMs but not cervical cancer cell lines. Human peripheral blood monocytes were differentiated into uncommitted macrophages (M0) and then polarized to M1, M2a, M2b, and M2c macrophages using LPS plus IFNr, IL-4, LPS plus IL1β, and IL-10, respectively. Using flowcytometry, we found CD80++ was the marker of M1 and M2b, CD206++ was the marker of M2a, and CD163++ was the marker of M2c, compared with M0 macrophages. By regulating CCL22, we found that the mean fluorescence intensity (MFI) of CD206 in TAMs was significantly affected compared to the control group. Therefore, CCL22 could polarize TAMs of cervical cancer toward M2a macrophages. In conclusion, our study revealed that CCL22 could be a therapeutic target for cervical cancer, which might be because of its role in regulating macrophage polarization.
Framework of Intellectual Capital-Based View in Improving Firm Agility

A hypercompetitive and unpredictable business environment requires companies to have resources that enable organizations to be proactive and responsive to the environment and improve organizational efficiency. By using library research methods, this paper tried to synthesize the theory of intellectual capital and resource-based view and then develop the indicators to be more specific. The results of the study showed that the dimensions of the intellectual capital-based view turned out as the support and guide for implementing agility in the company, and the firm agility will be more achievable if it has an intellectual capital-based view.
LCLS-II 1.3 GHz cryomodule design - lessons learned from testing at Fermilab

Fermilab’s 1.3 GHz prototype cryomodule for the Linac Coherent Light Source Upgrade (LCLS-II) has been tested at Fermilab’s Cryomodule Test Facility (CMTF). Aspects of the cryomodule design have been studied and tested. The cooldown circuit was used to quickly cool the cavities through the transition temperature, and a heater on the circuit was used to heat incoming helium for warmup. Due to the 0.5% slope of the cryomodule, the liquid level is not constant along the length of the cryomodule. This slope as well as the pressure profile caused liquid level management to be a challenge. The microphonics levels in the cryomodule were studied and efforts were made to reduce them throughout testing. Some of the design approaches and studies performed on these aspects will be presented. Fermilab is operated by Fermi Research Alliance, LLC under Contract No. De-AC02-07CH11359 with the United States Department of Energy. This work was supported, in part, by the LCLS-II Project.
Pandemi dönemi çevrimiçi satın alma davranışında finansal yetenekler ve teknolojik uygulamalar için öneriler: Türkiye’den kanıtlar

Bu çalışma, pandemi döneminde çevrimiçi satın alma davranışına etki eden unsurları saptamayı amaçlamaktadır. Yani pandemi döneminde ortaya çıkan pandemik kaygının finansal yeteneklerin ve teknoloji kullanımının çevrimiçi satın almadaki rolü Türkiye özelinde irdelenmektedir. Çalışmada Türkiye’de yer alan çevrimiçi satın almayı en az bir kere kullanmış bireyler örneklem olarak belirlenmiştir. Nicel desenli çalışmada SPSS paket programı ile açımlayıcı faktör, korelasyon, çoklu regresyon ve farklılık testleri kesitsel veriler toplanarak değerlendirilmiştir. Açımlayıcı faktör analizi sonuçlarına göre, finansal yetenekler mobil bankacılık kullanımı, ödeme ve risk toleransına yönelik tutum, finansal tavsiye, finansal hizmet riskine yönelik tutum ve finansal tutum boyutlarında toplanmıştır. Pandemik kaygı tek boyutta toplanmıştır. Teknoloji kullanımı ise, akıllı telefon kullanımı ve sosyal medya kullanımı faktörlerine ayrılmıştır. Çoklu regresyon analizi sonuçlarına göre, dijital bankacılık kullanımı, finansal tutum, akıllı telefon kullanımı, sosyal medya kullanımı ve pandemik kaygının çevrimiçi satın alma üzerinde istatistiksel olarak anlamlı ve pozitif yönde bir etkisi olduğu saptanmıştır. Ödeme ve risk toleransına yönelik tutumun ise çevrimiçi satın alma üzerinde anlamlı düzeyde ve negatif yönde bir etkisi bulunmuştur. Ayrıca önceki bankacılık deneyiminin ve eğitim düzeyinin çevrimiçi satın almada önemli bir rol oynadığı tespit edilmiştir.