bluuebunny/crossref_metadata_2025 huggingface dataset:
Penerapan Model Pembelajaran Flipped Classroom pada Mata Pelajaran Dasar-Dasar Konstruksi Bangunan dan Teknik Pengukuran Tanah
Authors: Wahyu Widiantara Fauzi , Daryati Daryati , Rosmawita Saleh
Published: June 2023

Abstrak:Penelitian ini bertujuan untuk mengetahui efektivitas dengan cara penerapan flipped classroom dalam mata pelajaran Dasar-Dasar Konstruksi dan Properti. Metode penelitian yang digunakan dalam penelitian ini adalah quasi experimental dengan bentuk randomized pretest-posttest control group design. Pengumpulan data dilakukan dengan instrument pretest dan posttest yang diberikan pada dua kelas, eksperimen dan kontrol. Uji statistik yang digunakan adalah statistik non-parametrik dengan uji Mann-Whitney U, didapatkan nilai Asymp.Sig (2-tailed)<𝖺𝑡𝑎𝑏𝑒𝑙 (0,05) yang berarti terdapat perbedaan signifikansi data posttest kelas eksperimen dan kelas kontrol. pembelajaran berbasis multimedia tersebut masuk dalam kategori average atau cukup efektif. Hasil penelitian menunjukan bahwa terjadi peningkatan pada kelas eksperimen yang diberikan treatment dengan  menerapkan flipped classroom pada platform edmodo, dibandingkan dengan kelas kontrol yang tidak diberikan treatment. Dengan demikian dapat disimpulkan bahwa  flipped classroom pada platform edmodo efektif dalam meningkatkan hasil belajar yang signifikan pada mata pelajaran Dasar-Dasar Konstruksi dan Teknik Pengukuran Tanah.
Abstract: This study aims to determine the effectiveness of the application of the flipped classroom in the subject of Construction and Property Fundamentals. The research method used in this study is a quasi-experimental with the form of a randomized pretest-posttest control group design.Data was collected using pretest and posttest instruments given to two classes, experimental and control. The statistical test used is non-parametric statistics with the Mann-Whitney U test, the value of Asymp.Sig (2-tailed) <𝖺𝑡𝑎𝑏𝑒𝑙 (0.05) means that there is a significant difference in the posttest data of the experimental class and the control class. The multimedia-based learning is categorized as average or quite effective  The results showed that there was an average increase in learning outcomes of 58% in the experimental class that was given treatment by applying the flipped classroom on the Edmodo platform, compared to the control class that was not given treatment. Thus, it can be concluded that the flipped classroom on the Edmodo platform is effective in increasing significant learning outcomes in the subjects of Construction Fundamentals and Soil Measurement Techniques.
From Prescription to Treatment: The Disciplinary (under)Achievement of IR in Turkey
Authors: SULA İsmail Erkam , SARI Buğra , LÜLECİ-SULA Çağla
Published: June 2023

International Relations (IR) in Turkey has been assessed by scholars on topics,
including but not limited to the need to increase contributions from Turkish IR
scholars to theoretical discussions, the need for homegrown theorizing, and
to improve the methodological quality of IR research originating in Turkey.
This literature has revolved around the diagnosis of and prescriptions for
what is referred to as the ‘disciplinary underachievement’ of IR in Turkey.
Recently, an increasing number of scholars have focused on disciplinary self-reflection
discussing the limitations and prospects in the state of IR discipline
in Turkey. Adding to this emergent literature, this paper identifies the reasons
for the ‘disciplinary underachievement’ in Turkish IR. The paper discusses
the conditions that hamper IR education in Turkey under three groups: 1) the
structure and content of undergraduate and graduate curricula, 2) the state of IR
as an academic discipline in Turkey, and 3) the state of IR literature in Turkish.
The paper also offers suggestions for a prospective treatment to improve the state
of the IR discipline and pedagogy in Turkey. It argues that an improvement in the
quality of IR education has significant potential to contribute to further inclusion
of locally produced IR knowledge into ‘global IR,’ which is widely cited in the
existing literature as a significant sign of ‘disciplinary progress.’
Biomedical Engineering Students’ Perceived Learning Through Co-Curriculars
Authors: Jamison Cassandra , Lattuca Lisa R. , Daly Shanna R. , Huang-Saad Aileen
Published: June 2023

Background: Co-curricular student outcomes research has focused on connecting outcomes to activities based on the co-curricular type. Less work has explored what aspects of those co-curricular activities could lead to student outcomes.
Purpose: Our research aimed to identify common elements of co-curricular activities that connected to students’ development of professional, career, or personal outcomes and can inform how we study and design co-curricular activities in engineering.
Design: We recruited participants from one biomedical engineering (BME) program. We used a one-year series of four semi-structured interviews with fourteen upper-level BME students to explore students’ perceptions of their co-curricular learning. Using a qualitative, causal analysis approach, we identified elements of students’ co-curricular experiences in research or a multi-disciplinary design team, as well as other co-curricular experiences (e.g., internships, professional societies), that linked to professional, career, or personal learning outcomes that have been previously identified as important in engineering education.
Findings: We identified patterns of connections between unique “experience elements” and a variety of “outcome categories” through participant activities we called “participant actions.” The most prevalent connections—those experience elements and participant actions that connected to multiple outcome categories—included the experience elements Independent Project Work, Project Work That Engages Multiple Disciplines, STEM Education Opportunities, and Mentorship from a Skilled Other as well as a participant action Reflecting on Experience. We found connections to the outcome categories of Leadership, Design, Business, Interdisciplinary Competence, Disciplinary Competence, Communication, and Career Direction Outcomes.
Conclusions: Based on our findings, educators and mentors should consider the value of supporting students’ decision-making autonomy and multidisciplinary interactions in projects to support learning. They could also incorporate opportunities for students to teach each other technical content, receive structured mentorship, and reflect on their experiences as they are happening. Further, this work demonstrates a need to explore co-curricular learning processes in new ways that can lead to better understandings of students’ learning processes.
Advance Directives in the Emergency Department – a Systematic Review of the Status Quo
Authors: WEBER Vincent , HÜBNER Aurelia , SCHAMBERGER Lukas , SOMASUNDARAM Rajan , BOEHM Lennert , BAUER Wolfgang , DIEHL-WIESENECKER Eva
Published: June 2023

Background Providing individualised healthcare in line with patient wishes is a particular challenge for emergency healthcare professionals. Documentation of patient wishes (DPW), e.g., in the form of advance directives, can guide clinicians in making end-of-life decisions that respect the patient’s wishes and autonomy. However, these are hindered by limited availability in emergency settings.Objective This systematic review aims to congregate existing data on DPW possesion and availability in the emergency department (ED) as well as contributing factors.Methods We searched the MEDLINE database (PubMed) in October 2021. All publications that provided primary quantitative data on DPW in the ED were assessed, culminating in a total of 16 studies included in the analysis. Most (n = 9) were from the US, followed by Australia (4), Germany (1), Canada (1) and Switzerland (1). Publication dates ranged from 1996 to 2020.Results In the general adult population presenting to the ED, 19.9–27.0% of patients possessed some variation of DPW, fewer than 3.2% had it available on presentation. In older people, possession rates (7.9–51.9%) as well as availability (1.7–48.8%) varied widely. The following variables were identified as positive predictors for DPW possession: older age, poorer overall health and presence of comorbidities, as well as several sociodemographic factors, such as female gender, having children, being in a relationship and higher level of education.Conclusion Possession and availability of DPW among ED patients was low in general and even in the older population mostly below 50%. While we were able to gather data on prevalence and predictors, we believe that further research is needed to explore the quality of DPW and possible public health measures to encourage patients to document their healthcare wishes.
Probabilistic Graph Networks for Learning Physics Simulations
Authors: Prakash Sakthi , Tucker Conrad
Published: June 2023

Inductive biases play a critical role in enabling Graph Networks (GN) to learn particle and mesh-based physics simulations. In
this paper, we propose two generalizable inductive biases that minimize rollout error and energy accumulation. Conditioned
on the input states, GNs currently assume Gaussian distributed targets. As a consequence, GNs either assign probability
densities to infeasible regions in the state space of the physics problem or fails to assign densities to feasible regions. Instead, we replace the existing assumption with a stronger assumption by estimating the true conditional target densities using our proposed conditional normalizing flows (cNF) decoder. We discover that this inductive bias enables GN to significantly improve its next state prediction accuracy. Existing sequential GNs encode temporal dependencies by autoregressively processing the latent representations of the input data. In our work, we discover that inducing the Arrow-of-Time inductive bias through an auto-regressive encoding step before autoregressively processing the resulting latent vectors enables GNs to better minimize rollout error. We critically analyze the impact of existing inductive biases on rollout error and energy accumulation and discover that the choice of biases to be encoded in a GN as opposed to the number of inductive biases has a substantial impact on forward simulation prediction.
A Simple-Structured Framework for Decision Support System in Irrigation Water Management: Tool Description and Preliminary Testing
Authors: Garofalo Pasquale , Vonella Alessandro Vittorio , Rinaldi Michele
Published: June 2023

In the context of climate change, where precipitation is decreasing and poorly distributed over time, and the cost of irrigation water is increasing, an efficient and sensible water supply system is critical to reduce water waste without compromising crop productivity. To achieve this, a system that assists farmers in irrigation scheduling and management must be easy to understand, apply, and interpret, and be highly adaptable to the practices actually used by farmers in the field. This paper describes an irrigation scheduling decision support system that uses limited algorithms and computational routines to formalize a few parameters related to crop development, productivity, and water use for irrigation scheduling. The system predicts when and how much to irrigate based on three methods for determining crop water requirements and their effects on crop development and yield performance. The system was calibrated and tested on tomato plants grown in a Mediterranean environment. In this first benchmark, it has shown high robustness and reliability in replicating the studied cropping system and optimizing the use of irrigation resources.
Sensor placement for leak localization in water distribution networks based on graph sampling method
Authors: Li Juan , Cai Baoyi , Wang Chunyue
Published: June 2023

The sensor placement is an important research issue for monitoring water distribution networks (WDN). Due to the natural graphical structure of the WDN, it is advantageous to use graph sampling theory for selecting monitoring nodes in the WDN. But the existing graph sampling theory is only applied to processing the band-limited signal, and the pressure data of WDN is a non-band-limited signal. This paper is devoted to solving this problem. The paper proposes an approximate conversion method from non-band-limited signal to band-limited signal and gives an optimal spectrum threshold formula. The threshold formula is applied to perform spectral screening in the graph frequency domain and to convert a non-band-limited signal into a band-limited signal. The band-limited signal retains the major frequency components of the original signal and ignores the frequency components of smaller values. The paper performs graph sampling of the obtained band-limited signal and obtains sampling nodes that can perfectly recover the band-limited signal. The sampling node is used as the monitoring node of the WDN to obtain comprehensive information about the WDN. Our method compares numerically with two methods of optimizing sensor placement. The experiment results demonstrate the effectiveness of the proposed method.
A Knowledge-Based System For Smart Sustainable Groundwater Facility Management
Authors: Ataei Parisa , Takhtravan Amir , Gheibi Mohammad , Faramarz Mahdieh G. , Wacławek Stanisław , Fathollahi-Fard Amir M. , Behzadian Kourosh
Published: June 2023

Monitoring and supervising groundwater resource facilities, including wells and pumps, are the most challenging management issues for both academia and industrial practitioner working in water management. These motivate this study to propose an intelligent Decision Support System (DSS) to interpret the huge data records for operating propositions authorized to decide based on the provided information. In this work, an integrated database of the influencing parameters, including water flow rate, water pressure, current intensity, voltage, and power of the wells and pumps, have been gathered by telemetry arrangements as a Knowledge-Based Systems (KBS). Statistical appraisals are carried out on these parameters in six randomly selected wells to define the thresholds of these effective factors. Then, a soft-sensor is designed using Random Forest (RF) machine learning prediction algorithm to forecast water flow rate, water pressure, and current intensity in wells. In this soft-sensor, online comparison of the achieved data from telemetry system with design catalogs of pumps and periodic field tests conducted on the wells and their facilities have provided an empirical framework for health monitoring of wells and pumps. Finally, a framework of management knowledge and operational experience of professionals at water and Wastewater companies generated by applying the Classical Delphi (CD) technique. The outcome of this work has been presented as the managerial insights for the wells and pumps monitored online with high precision.
Characterization of two cDNAs encoding pH-sensitive and zinc-gated chloride channels in the fall armyworm, Spodoptera frugiperda
Authors: Wang Wei , Chen Jiasheng , Niu Duobang , Zhang Mohan , Cao Haiqun , Palli Subba , Sheng Chengwang
Published: June 2023

The pH-sensitive chloride channels (pHCls) are unique chloride channels in invertebrates and have important roles in regulation of fluid secretion, food selection and intake. pHCls are widely expressed in insects, but little is known about their pharmacological properties and their sensitivity to metal ions. Herein, we isolated two cDNAs (Sfphcl1 and Sfphcl2) that encode SfpHCl1 and SfpHCl2 subunits from the fall armyworm Spodoptera frugiperda. The Sfphcl1 and Sfphcl2 demonstrated similar expression patterns with most abundant expression in the Malpighian tubules of the first instar larval stage. The cRNA of Sfphcl1 and Sfphcl2 were injected into Xenopus laevis oocytes singly or together in three different ratios of 1:4, 1:1 and 4:1 to characterize their function and investigate their zinc ion sensitivity. We found that SfpHCl1 and SfpHCl2 formed chloride channels in oocytes with a reversal potential that is consistent with chloride selectivity, but showed insensitivity to changes in external sodium concentrations. The extracellular pH shift and zinc-elicited inward currents in oocytes expressing SfpHCl1 and SfpHCl2 showed a similar EC50. These results provide the biophysical and pharmacological properties of pH-sensitive, zinc-gated chloride channels. Since the pHCls are present only in invertebrates, they may provide an ideal target for highly specific insecticides.
Seagrass as a Nutraceutical Agent against Proinflammatory Markers
Authors: mathakala Vani , Ullakula Tejaswini , Palempalli Uma Maheswari Devi
Published: June 2023

Background
The Pro-inflammatory mediators such as prostaglandins (PGE2), nitric oxide and Tumor necrosis factor (TNF-α) are the key players in the stimulation of the inflammatory responses. Thus, the pro inflammatory mediators are considered to be potential targets for screening nutraceutical with anti-inflammatory activity.
Methods
In this context, we explored the potency of seagrass extract by using lipopolysaccharide stimulated RAW 264.7 murine macrophages as an experimental model. The anti-inflammatory activity of seagrass was assessed through the down regulation of marker enzymes of inflammation such as COX-2 and nitric oxide and also the inhibition of pro inflammatory mediators.
Results
The phytochemical constituents of seagrass namely Isocoumarin, Hexadecanoic acid, and Cis-9 Octadecenoic acid, 1,2 Benzene dicarboxylic acid and beta-sitosterol were docked with TNF-alpha, COX-2, iNOS and PGES-1 by using Mastero 13.0 software to establish the potential of seagrass metabolites on the modulation of pro inflammatory enzymes and mediators and to prove the significance of seagrass as nutraceutical agent for inflammation.
Conclusions
The methanolic extract of seagrass Halophila beccarii is a potential nutraceutical agent to fight against inflammation with a significant anti-inflammatory activity by controlling the secretion of pro inflammatory mediators such as TNF-alpha, COX-2, iNOS and mPGES.Thus, Inflammation is resolved by regulating the inflammatory pathway mediated by PGE2, TNF-α, NO and down regulation of COX-2 and iNOS.
Adaptative Diffraction Image Registration
for 4D-STEM to optimize ACOM Pattern Matching
Authors: Demortiere Arnaud
Published: June 2023

The technique known as 4D-STEM has recently emerged as a powerful tool for the local characterization of crystalline structures in materials, such as cathode materials for Li-ion batteries or perovskite materials for photovoltaics. However, the use of new detectors optimized for electron diffraction patterns and other advanced techniques requires constant adaptation of methodologies to address the challenges associated with crystalline materials. In this study, we present a novel image processing method to improve pattern matching in the determination of crystalline orientations and phases. Our approach uses sub-pixelar adaptative image processing to register and reconstruct electron diffraction signals in large 4D-STEM datasets. By using adaptive prominence and linear filters such as mean and gaussian blur, we are able to improve the quality of the diffraction pattern registration. The resulting data compression rate of 103 is well-suited for the era of big data and provides a significant enhancement in the performance of the entire ACOM data processing method. Our approach is evaluated using dedicated metrics, which demonstrate a high improvement in phase recognition. Our results demonstrate that this data preparation method not only enhances the quality of the resulting image but also boosts the confidence level in the analysis of the outcomes related to determining crystal orientation and phase. Additionally, it mitigates the impact of user bias that may occur during the application of the method through the manipulation of parameters.
Association between Alcohol Consumption Frequency, Coffee, Cheese Intake, and Anxiety with the Risk of Gastroesophageal Reflux Disease: A Mendelian Randomization Study
Authors: Zhang Qingqing , Liu Nanyang , Wu Di , Xu Zhengyu , Wang Yichen , Wang Ping
Published: June 2023

Background
In previous observational research, an association has been found between the frequency of alcohol consumption, coffee intake, cheese consumption, and anxiety with the risk of gastroesophageal reflux disease (GERD). However, conflicting conclusions exist among these studies, and the causal relationship between these exposure factors and GERD remains uncertain.
Methods
Independent genetic variants associated with alcohol consumption frequency, coffee intake, cheese consumption, and anxiety at the genome-wide significance level were selected as instrumental variables. Summary-level data for GERD was derived from a genome-wide association meta-analysis, which included 78,707 cases and 288,734 European-ancestry controls. The primary analysis method was Inverse Variance-Weighted (IVW), with Weighted Median (WM), MR-Egger, Simple mode, and Weighted mode methods serving as complementary approaches to IVW. Sensitivity analyses were conducted using Cochran's Q test, the MR-Egger intercept test, and leave-one-out analysis to assess the stability of the results.
Results
The IVW results demonstrate a strong positive causal relationship between the frequency of alcohol intake (OR=1.52, 95%CI=1.25-1.84, P<0.001) and having consulted a general practitioner for nerves, anxiety, tension, or depression (OR=22.60, 95%CI=12.12-42.15, P<0.001) with GERD. A negative causal relationship was observed between genetically predicted cheese consumption and GERD (OR=0.36, 95%CI=0.26-0.50, P<0.001). However, the association between coffee consumption and GERD was not significant in the IVW analysis (OR=1.21, 95% CI, 0.98-1.60, P>0.05).
Conclusions
This study reveals the causal relationships between the frequency of alcohol consumption, cheese intake, and anxiety with GERD, as well as the potential role of high coffee consumption in the development of GERD.
A rapid and positive effect of coastal marine reserves: the example of the Palavas Marine Reserve (France)
Authors: Molinier Pauline , Mallet Alicia , Jouvenel Jean-Yves , Changeux Thomas
Published: June 2023

The aim of this article is to study the early effects of a recent marine reserve on the fish population, the Palavas Coastal Marine Reserve (PCMR), created in 2016 on fishermen initiative. This recent reserve, covering 100 ha and located 2.6 km from the coast at N 43°30.6845, E 3°58.4635, constitutes almost entirely a protected zone, with a ban on any fishing activity. The abundance of the fish populations and the size and biomass of the target species have been studied for the period of the first 4 years of protection. An inventory of fish populations was carried out using the scuba diving transect method in the rocky substrate of three zones: a large enhanced protection zone (EPZ) where only navigation was allowed,, a small restricted zone (RZ), where scuba diving was admitted, and an off-reserve zone (ORZ). Monitoring of this recent reserve shows significant increases in overall abundance and changes in population assemblages within the third year of protection. The biomass of target species tripled in the EPZ showing a refuge effect despite the fact that the fishing ban was not always respected during this implementation period. However, the behaviour patterns of the fish, which are more or less fearful of divers depending on the study area, do not offer an adequate basis for determining differences in populations between the EPZ and the RZ.
Assessing the Statistical Abilities of GPT-4 as a Zero-shot Reasoner: Strengths and Weaknesses
Authors: Costa Douglas , Dias João , Nakano Celso , Monteiro Mario Luiz
Published: June 2023

Background
The field of artificial intelligence (AI) has witnessed remarkable advancements in natural language processing and understanding (NLP and NLU), particularly through the development of large language models like GPT-4. These models have demonstrated promise across various domains, including medicine. However, the extent to which they can reason statistically as zero-shot reasoners remains largely unexplored.
Objective
This study aims to evaluate GPT-4's statistical abilities as a zero-shot reasoner and identify its strengths and weaknesses in addressing statistical inquiries.
Methods
A diverse set of statistical questions was extracted from published articles and inputted into the GPT-4 chatbot. The responses generated by GPT-4 were assessed for accuracy and compared against the correct answers. Logistic regression analyses were performed to determine the impact of statistical topics and AI tasks on the model's performance.
Results
GPT-4 achieved an overall accuracy of 74% in responding to the statistical questions. The analysis revealed that the model excelled at comprehending well-structured and unambiguous questions, showcasing proficiency in entity recognition and information integration. However, it encountered difficulties with complex statistical concepts, data interpretation, and questions involving ambiguity or convoluted structures.
Conclusion
GPT-4 demonstrated strengths in understanding statistical concepts when presented clearly. However, it faced challenges with more intricate tasks and synthesizing information from multiple sources. Suggestions for improvement include fine-tuning the model using advanced statistical datasets, incorporating external knowledge sources, optimizing prompt engineering techniques, and enabling visual information processing.
Implications: This study offers insights into the strengths and weaknesses of GPT-4 as a zero-shot reasoner in statistical tasks. Although the model exhibits potential in basic statistical reasoning, caution should be exercised in relying solely on its responses without human supervision for comprehensive statistical analysis and interpretation. Additionally, given that most researchers in the medical field may lack statistical expertise, leveraging language models can be valuable for addressing their statistical inquiries.
Exercise-primed extracellular vesicles improve cell-matrix adhesion and chondrocyte health
Authors: Iijima Hirotaka , Wang Kai , D'Amico Ella , Tang Wan-Yee , Rogers Renee J. , Jakicic John M. , Ambrosio Fabrisia
Published: June 2023

Extracellular vesicles (EVs) have been suggested to transmit the health-promoting effects of exercise throughout the body. Yet, the mechanisms by which beneficial information is transmitted from extracellular vesicles to recipient cells are poorly understood, precluding a holistic understanding of how exercise promotes cellular and tissue health. In this study, using articular cartilage as a model, we introduced a network medicine paradigm to simulate how exercise facilitates communication between circulating EVs and chondrocytes, the cells resident in articular cartilage. Using the archived small RNA-seq data of EV before and after aerobic exercise, microRNA regulatory network analysis based on network propagation inferred that circulating EVs activated by aerobic exercise perturb chondrocyte-matrix interactions and downstream cellular aging processes. Building on the mechanistic framework identified through computational analyses, follow up experimental studies interrogated the direct influence of exercise on EV-mediated chondrocyte-matrix interactions. We found that pathogenic matrix signaling in chondrocytes was abrogated in the presence of exercise-primed EVs, restoring a more youthful phenotype, as determined by chondrocyte morphological profiling and evaluation of chondrogenicity. Epigenetic reprograming of the gene encoding the longevity protein, α-Klotho, mediated these effects. These studies provide mechanistic evidence that exercise transduces rejuvenation signals to circulating EVs, endowing EVs with the capacity to ameliorate cellular health even in the presence of an unfavorable microenvironmental signals.
Hydropower Scheduling with Power Load Prediction: Optimizing Energy Efficiency and Navigation Performance
Authors: Huang Guangqin , Tan Ming , Meng Zhihang , Yan Jiaqi , Chen Jin , Qu Qiang
Published: June 2023

Hydropower stations integrated into the grid system often suffer from imbalanced scheduling of power generation and shipping benefits due to untimely acquisition of load data. This paper proposes a joint scheduling model for hydropower stations based on power load forecasting and applies it practically to the Shatuo Hydropower Station in Guizhou Province of China. The model uses forecasting algorithms to predict power load data and optimization algorithms to schedule the discharge flow for each time period. Experiments show that the CNN-GRU model (i.e., the Convolutional Neural Network - Gate Recurrent Unit) is superior to other models in load balancing data for water stations. Using predicted power load data and the GA-NSGA-II algorithm (i.e., the improved elite non-dominated sorting genetic algorithm), the scheduling results are optimized, making the Shatuo Hydropower Station achieve both power generation and navigation benefits. This approach solves the problems of untimely load data acquisition and insufficient scheduling, providing an effective way for hydropower generation navigation scheduling.
Detecting faulty lithium-ion cells in large-scale parallel battery packs using current distributions
Authors: Lambert Pierre , Tredenick Eloise , Duncan Stephen , Drummond Ross
Published: June 2023

One of the main issues affecting the uptake of battery packs are safety concerns, particularly with respect to the fires caused by cell faults. Managing the risks from faults requires advances in battery management systems and an understanding of the dynamics of large packs. To address this issue, a machine learning classifier based upon a support vector machine was developed to detect cell faults within large packs using a limited number of current sensors. To train the classifier, a modelling framework for parallel connected packs was introduced and shown to generalise to Doyle-Fuller-Newman electrochemical models. The fault classification performance was found to be satisfactory, with an accuracy of 83% using current information from only 27% of the cells. These results highlight the potential of combining mathematical modelling and machine learning to improve battery management systems and deal with the complexities of large packs.
Improving Drought Resistance by Introduction of the Proline Synthesis Gene P5CSA into Inbred Rice Lines as a New Genetic Resource for Breeding Programs
Authors: Herawati Reny , Masdar Masdar , Sutrawati Mimi , Simarmata Marulak , Fahrurrozi Fahrurrozi
Published: June 2023

This research was aimed to identifying the P5CS gene involved in the drought stress mechanism in upland rice lines which is candidate as new genetic resource for breeding programs. The plant material consisted of 19 breed lines: Salumpikit and IR20 varieties, drought-tolerant and sensitive, respectively. The experiment consisted of 4 stages, including the evaluation of drought stress with 20% PEG 6000 (-0.58 MPa) in the germination and nursery phases, the vegetative phase, and the expression analysis of the P5CS gene. The results showed that the PEG inhibited the growth of roots, shoots, and the ratio of roots to shoot in the germination and nursery phases of all the tested lines, while the Salumpikit and IR20 varieties were confirmed as drought resistant and sensitive, respectively. The proline content under drought stress was significantly different in the lines tested, while Salumpikit and IR20 were confirmed to have high and low proline content, respectively. The proline content in several lines, such as G4, G6, G8, G10, G12, G13, G14, G15, and G17, exceeded the content in the Salumpikit variety. The P5CS gene was amplified in PCR analysis and expressed in the consistency of proline. It was found that the lines of G4, G6, G8, G13, and G17 showed tolerance to drought stress, had high STI values, and showed recovery ability and proline content. These lines have the potential to be released as candidates for new varieties. In addition, these lines have great potential as a new genetic source for upland rice breeding programs.
Does fiscal devaluation always work? A sectoral and business cycle perspective
Authors: Cizkowicz Piotr , Rzońca Andrzej , Wojciechowski Wiktor
Published: June 2023

The study verifies effects of fiscal devaluation on a broad set of sector and firm-level macroeconomic variables among European economies in years 1995-2019. Using local projection and panel data models it finds that fiscal devaluation impact on employment is stronger in services and small businesses, where production is most labour intensive. In turn, in manufacturing, where production is capital intensive, firms may substitute capital for labour in response to fiscal devaluation. Lastly, fiscal devaluation favours employment in recessions more than in times of economic expansions, as only in recessions it reduces labour costs in a more lasting way.
JEL codes: C33, E24, E62, E63, J50, H30, H60
ZmLLG1 gene affects the development of the maize root system
Authors: Sun Siyu , Yang Yulu , Shan Richard , Wu Hao , Xie Hongxue
Published: June 2023

Nutrient uptake by plant roots seriously affects the growth and yield of maize. AUX/IAA encoding genes play an important role in auxin signal transduction and regulating the growth of plant roots.In this study, AUX/IAA gene ZmLLG1 was cloned from maize. The expression level of the ZmLLG1 gene in different tissues was detected by qRT-PCR, and ZmLLG1 was found to be overexpressed in the roots of maize. Arabidopsis thaliana and mutant maize were both analyzed by statistical method. A yeast two-hybrid experiment, BiFC experiment and pull-down experiment were used to verify the interactions between the protein and ZmLLG1.The CoDing Sequence (CDS) of ZmLLG1 is 684 bp and encodes a protein composed of 227 amino acids. A subcellular localization analysis confirmed that ZmLLG1 was localized in the nucleus. The ZmLLG1 gene was expressed in all tissues of maize, but its expression level was highest in the root. The root length and number of lateral roots of zmllg1 mutant maize were much lower than those of wild-type B73 maize, and ZmLLG1 was responsive to auxin. The yeast two-hybrid assay, BiFC experiment and pull-down assay showed that ZmLLG1 could interact with ZmARF5, ZmARF7, and ZmARF25 to regulate the growth and development of the maize root system. Keywords AUX/IAA, Root, ARF, Maize mutant, Protein
Fear of hypoglycaemia among insulin-treated patients with type 2 diabetes mellitus: a cross-sectional study
Authors: Qiu Jiajia , Wang Panxia , Qin Nan , Lv Cheng , Liang Xinyu , Jiang Sheng
Published: June 2023

To analyze the occurrence and influencing factors of fear of hypoglycemia in type 2 diabetes mellitus treated with insulin. From June 2021 to June 2022, hospitalized T2DM patients with a history of hypoglycemia episodes in the past six months were randomly selected as research subjects in the First Affiliated Hospital of Xinjiang Medical University by convenient sampling, and paper questionnaires were distributed on the spot and collected on the spot by researchers who had received unified training, including general information questionnaire, hypoglycemic fear scale (HFS-II.) A total of 300 questionnaires were distributed, and 278 valid questionnaires were recovered, with an effective recovery rate of 92.7%. Among the 278 patients with T2DM, 171 were male, (61.5%), 107 were female, (38.5%), age 58 (53, 66) years, glycated hemoglobin 8.76% (7.4%, 10.32%), HFS-II total score was 19.5 (10.75, 31). The total scores of HFS-II. in T2DM patients with different disease course, BMI, gender ,ethnicity, hypoglycemia type, frequency of blood glucose monitoring, number of hypoglycemia in the past six months, and peripheral neuropathy lesions were significantly compared(P<0.05). The results of multiple linear regression analysis show that the regression equation is significant, F=13.119, P<0.001. Among them, ethnicity(Uygur B=1.036, P<0.001), blood glucose monitoring frequency (>3 times a week, B=1.196, P<0.001; ≤1 time per month, B=0.883, P<0.001; 2~3 times a month B=0.678, P=0.014), the number of occurrences of hypoglycemia in the past six months (3~4 times B=0.958,P<0.001;>6 times B=0.939, P<0.001), hypoglycemia type (severe hypoglycemia B=1.273, P=0.007;pseudohypoglycemia B=1.195, P<0.001;Symptomatic hypoglycemia B=0.592, P=0.029) was an influencing factor in FoH and explained 28.3% of the total variation (R2=0.306, adjusted R2=0.283). Ethnicity, the number of hypoglycemia occurrences in the past six months, the type of hypoglycemia, and the frequency of blood glucose monitoring are the influencing factors of FOH in T2DM patients. Medical staff should screen patients' psychology early, actively provide individualized treatment, strengthen diabetes education.
Prevention and Treatment of Neonatal Hypothermia through an Implementation Science Study in Jaltenango Chiapas, Mexico
Authors: Garcia Alejandro Frade , Azcarraga Lucila Servitje , Olivas María Azucena Espinosa , Ulloa Laila Zulema Garcia , Santisteban Rodrigo Garcia , Sosa Mariana Yulian Montano , Liu Enju , Hansen Anne
Published: June 2023

Introduction: Neonatal Hypothermia is preventable but common, contributing to neonatal morbidity and mortality especially in low resource settings. Kangaroo Mother Care (KMC) is the preferred method to prevent hypothermia, but relying on it as a continuous heat source is challenging. Other sources of external heat designed for low resource settings are an important potential complement to KMC. This study introduced a novel Infant Warmer in a low resource community hospital through an implementation science approach.
Methods: We conducted a prospective, interventional cohort study in Jaltenango Chiapas, Mexico from January to November 2022. Our intervention was 1) an educational program about the importance of euthermia and optimal thermoregulatory practices including KMC, and 2) provision of an Infant Warmer designed for low-resource settings with training of healthcare providers. Our hypothesis was that neonatal hypothermia rates would decrease after our intervention. Our aims were to reduce hypothermia, and increase knowledge and confidence regarding neonatal thermoregulation. The study had three phases: Pre-Intervention, Intervention, and Warmer Use. We collected clinical data during the Pre-Intervention and Warmer Use Phases, including temperature on admission and six hours later (called “Follow-Up”). At three-time points we conducted surveys of healthcare providers regarding their knowledge of hypothermia, confidence in keeping newborns warm, and attitudes regarding the Warmer. We also conducted a Parent Survey.
Results: We studied 372 newborns. Comparing Pre-Intervention to Warmer Use Phases, rates of hypothermia decreased from 62% to 27% on admission, and 59% to 11% on Follow-Up. The mean admission and Follow-Up temperatures increased by 0.06°C and 0.23°C (p=0.003) respectively. Healthcare providers' knowledge of hypothermia and confidence in keeping newborns warm also improved throughout the study.
Conclusion: We found high baseline rates of neonatal hypothermia in this low resourced hospital. We successfully lowered rates and improved knowledge of hypothermia by providing education and appropriate thermoregulatory equipment to complement KMC.
IRB-P00043372.
Trend Analysis for Different Types of Aerosols in Conjugation with Temperatures for the Indian Region During the Post-Monsoon Season (1980-2019)
Authors: Yadav Harsh , Mehta Manu , Jain Shruti , Singh Sandhya , Bhandari Shrishti , Nihlani Seema
Published: June 2023

This study has made an effort to understand the long-term changes of aerosol loadings as well as temperature in the post-monsoon season (October-November) over a 40-year long period (1980–2019) for the Indian region using MERRA-2 reanalysis data. Special emphasis has been given on the highly populated and polluted cities of Delhi, Mumbai, Kanpur, and Jaipur. The focus was put on the total Aerosol Optical Depth (AOD) and on that of Black Carbon (BC), Organic Carbon (OC) and Sulphates. The rapid urbanisation and increasing population of the cities have brought along increasing air pollution levels, and an increase in AOD levels, especially in the recent decades. The changes in temperature were analyzed by studying the air temperature at 2m height and the surface air temperature parameters. The temperatures, although at varying rates, have increased throughout the Indian region in the past decades. The long-term trend analysis of aerosols showed an increase in rapid rise in the AOD levels. Corresponding increase or decrease in temperature trends have been discussed.
Identification of Immune-Related Hub Genes in Multiple Myeloma
Authors: Sheng Xinge , Hong Xiuli , Lu Jingyuan , Huang Fangfang , Deng Huilan , Lu Quanyi
Published: June 2023

Purpose:: Multiple myeloma(MM) is a common malignant tumor in the blood system. Despite recent advances in its treatment, its symptomatic remission rate and survival rate are still not optimistic. In the future, it is necessary to continue to search for different treatment targets and new treatment methods in order to improve the quality of life and survival time of patients with MM. The study aims to explore the potential immune related pivotal genes and immune infiltration patterns in MM.
Methods: The study included peripheral blood samples from patients with MM who our hospital from October 2020 to April 2022. Obtain a gene chip for research from a comprehensive gene expression database, perform differential expression analysis on the processed gene dataset, and then perform functional enrichment analysis, weighted gene co expression network analysis, GSEA immune infiltration analysis, and LASSO regression analysis on the obtained differential expression genes to obtain the hub genes. Finally, the hub gene TNFSF14 (LIGHT) was validated by qRT-PCR.
Results: In the study, three immune-related hub genes (ADAM8, CR2, and TNFSF14) and three main types of peripheral immune cells (activated CD8 T cells, macrophages, and plasma cell like dendritic cells) were obtained, which are closely related to the pathogenesis of MM. Then, by collecting peripheral blood samples from some patients in our hospital and conducting real-time fluorescence quantitative polymerase chain reaction, it was confirmed that the hub gene TNFSF14 (LIGHT) mined in this study was highly expressed in peripheral blood samples from patients with MM, which may indicate that it plays a pathogenic role in MM.
Conclusion: The study found that immune-related hub genes (ADAM8, CR2, and TNFSF14) are closely related to the pathogenesis of MM, and should be further researched.
On the construct of subjective risk intelligence: relationships with personality, emotional intelligence and coping strategies. A comparison between adolescents and adults.
Authors: Guarnera Maria , Zarbo Rita , Buccheri Stefania Lucia , Magnano Paola
Published: June 2023

Background The complexity of today's scenario has made it necessary to investigate the need for individuals to make choices that entail increasing exposure to risk and uncertainty. Among the individual resources that could help people to cope with situations of uncertainty, the new construct of subjective risk intelligence, known as a person's ability to effectively weigh the pros and cons of a decision in situations where not all outcomes are foreseen, would seem to play a prominent role. Considering that personality and coping strategies have been shown to be significantly related in previous research, the present study investigates the relationship between subjective risk intelligence, emotional intelligence, personality traits and coping strategies in both adults and adolescents.Methods The cross sectional study was conducted on 1390 Italian people, divided into two subsamples: 641 adolescents and 749 adults.Results The results showed that subjective risk intelligence mediates the role that personality traits and emotional intelligence have on coping strategies, thus influencing the choice of effective or ineffective strategies in both adults and adolescents, highlighting several differences between the two groups.Conclusion Subjective risk intelligence could be activated in order to deal with uncertain and risky situations. Suggestions for future research and interventions were given.
Integrated Transcriptome and Protein-Protein Interaction Network Analysis Uncovers Pivotal Ribosomal Proteins and Ion Transporters Involved in Rice Salt Tolerance
Authors: Lelekami Mojdeh Akbarzadeh , Pahlevani Mohammad Hadi , Nezhad Khalil Zaynali , Mashaki Keyvan Mahdavi , Brilhaus Dominik , Weber Andreas P.M.
Published: June 2023

Salinity stress is a major challenge for rice production, especially at seedling stage. To gain a comprehensive insight into the molecular mechanisms and potential candidate genes involved in rice salinity stress response, we integrated RNA-Seq and protein-protein interaction (PPI) network analysis to investigate the transcriptome dynamics of two contrasting genotypes. We collected root and shoot tissue samples at two timepoints (6 hours and 54 hours) after exposure to salinity stress. A total of 15,483 differentially expressed genes (DEGs) were identified across different combinations studied. Salt-specific genes were identified by comparing the genotypes under salinity stress. These salt-specific genes were mainly involved in metabolic processes, response to stimulus, and transporter activity, and were enriched in key metabolic pathways such as, biosynthesis of secondary metabolites, plant hormone signal transduction, and carotenoid biosynthesis. The PPI network analysis revealed 50 and 25 hub genes for salt-specific genes in the salt-tolerant CSR28 and salt-sensitive IR28, respectively. These hub genes were mainly involved in ribosome and encoding of important ribosomal proteins such as, RPL5, RPL18 and RPS9 with a potential role in stress signaling and tolerance enhancement in CSR28. Furthermore, the expression patterns of ion transporter genes in the roots at 54-hour timepoint regulated the Na+/K+ balance in the shoot. We also identified key transcription factors (TFs) that exhibited specific expression patterns based on timepoint, organ, or genotype. Our study provides valuable information for further investigation of the candidate genes associated with salt tolerance and development of salt-tolerant rice varieties.
Factors associated with optimal uptake of sulphadoxine-pyrimethamine in pregnancy: a facility-based cross-sectional study in the Ningo-Prampram district of Ghana
Authors: Asiimwe Nashira , Diarra Youssouf , Anto Francis
Published: June 2023

Background: Malaria is endemic throughout Ghana, with children under five years and pregnant women being the most at risk of the severe form of the disease. The Ghana malaria control programme recommends a minimum of five doses of intermittent preventive treatment of malaria during pregnancy using sulphadoxine pyrimethamine (IPTp-SP). Available data show that IPTp-SP uptake in the Ningo-Prampram district is much lower than the regional and national averages.
Method:A facility-based cross-sectional analytic study was conducted to assess client and service provider factors associated with uptake of five doses of SP using the mixed method.
Results: A total of 457 nursing mothers who had delivered within a period of six months, aged 15- 45 years participated in the study. Uptake of five doses of SP was 15.3% (70/457) with 27 of the women (5.91%) not receiving any dose of SP. Among those who received the drug, 207 (48.14%) took the first dose at week 16 of gestation. The average number of ANC visits made was 5.71 (range 0- 13), with 26.7% (122/457) making the minimum recommended eight ANC visits. Seven of the women did not attend ANC at all during their most recent pregnancy. The gestational age at taking first dose of SP (AOR 0.31, 95% CI:0.15-0.62), the number of ANC sessions attended (AOR 3.8, 95% CI: 2.05-7.05) and the level of knowledge of the mother about IPTp-SP (AOR 2.51, 95% CI:1.25-5.04) were significantly associated with receiving five doses of SP.
Conclusion: The level of uptake of five doses of SP was low. Encouraging women to initiate ANC early during pregnancy and also to make more visits through health education by midwives could help improve uptake of IPTp-SP in the Ningo-Prampram district of Ghana and other similar settings.