bluuebunny/crossref_metadata_2025 huggingface dataset:
Construction of a predictive model for blood transfusion in patients undergoing total hip arthroplasty and identification of clinical heterogeneity
Authors: Deng Jicai , Zhou Chenxing , Xiao Fei , Chen Jing , Li Chunlai , Xie Yubo
Published: January 2024

A precise forecast of the need for blood transfusions (BT) in patients undergoing total hip arthroplasty (THA) is a crucial step toward the implementation of precision medicine. To achieve this goal, we utilized supervised machine learning (SML) techniques to establish a predictive model for BT requirements in THA patients. Additionally, we employed unsupervised machine learning (UML) approaches to identify clinical heterogeneity among these patients. In this study, we recruited 224 patients undergoing THA. To identify factors predictive of BT during the perioperative period of THA, we employed LASSO regression and the random forest (RF) algorithm as part of supervised machine learning (SML). Using logistic regression, we developed a predictive model for BT in THA patients. Furthermore, we utilized unsupervised machine learning (UML) techniques to cluster THA patients who required BT based on similar clinical features. The resulting clusters were subsequently visualized and validated. We constructed a predictive model for THA patients who required BT based on six predictive factors: Age, Body Mass Index (BMI), Hemoglobin (HGB), Platelet (PLT), Bleeding Volume, and Urine Volume. Before surgery, 1 h after surgery, 1 day after surgery, and 1 week after surgery, significant differences were observed in HGB and PLT levels between patients who received BT and those who did not. The predictive model achieved an AUC of 0.899. Employing UML, we identified two distinct clusters with significantly heterogeneous clinical characteristics. Age, BMI, PLT, HGB, bleeding volume, and urine volume were found to be independent predictors of BT requirement in THA patients. The predictive model incorporating these six predictors demonstrated excellent predictive performance. Furthermore, employing UML enabled us to classify a heterogeneous cohort of THA patients who received BT in a meaningful and interpretable manner.
Endocrine and dog factors associated with semen quality
Authors: Hallberg Ida , Olsson Hannah , Lau Angus , Wallander Stina , Snell Anna , Bergman Daniel , Holst Bodil Ström
Published: January 2024

Knowledge of factors associated with semen quality may help in investigations of the aetiology and pathophysiology. We investigated the correlation between biomarkers for testicular cell function (anti-müllerian hormone, AMH, Inhibin B, testosterone, free androgen-index (testosterone/sex-hormone binding globulin), insulin like peptide 3, INSL-3), alkaline phosphate (ALP), canine prostate-specific esterase (CPSE), and heterophilic antibodies with dog variables, semen quality, and fertility. Blood and semen were collected from 65 Bernese Mountain Dogs. We evaluated total sperm count, motility and morphological parameters. The semen quality ranged from poor to excellent, with an average total sperm count of 1.1 × 109 and 50% morphologically normal spermatozoa (MNS). Age and abnormal testicular consistency correlated with decreased motility and MNS. Higher ALP correlated with higher total sperm count. AMH could not be detected in seminal plasma. AMH in blood correlated with head defects and high AMH concentration correlated with a severe decline in several semen parameters. Testosterone was negatively and CPSE positively correlated with age. No correlations were found for INSL-3, inhibin B, or heterophilic antibodies. Our findings contribute to the understanding of factors associated with semen quality in dogs, particularly related to Sertoli cell function.
Modified silica-based double-layered hydrophobic-coated stainless steel mesh and its application for oil/seawater separation
Authors: Deachophon Aunchalee , Bovornratanaraks Thiti , Poompradub Sirilux
Published: January 2024

A double-layered hydrophobic-coated stainless steel mesh (CSSM) was successfully prepared by vapor deposition of polydimethylsiloxane (PDMS) to form aerosol silica (SiO2) particles on SSM followed by coating with the in situ modified SiO2 generated in the natural rubber (NR) latex for use in oil/seawater separation. The in situ SiO2 particles were modified with octyltriethoxysilane (OTES) or hexadecyltrimethoxysilane (HDTMS). Transmission electron microscopy, 29Si solid-state nuclear magnetic resonance, and Fourier transform infrared spectroscopy were used to determine the structure of the in situ modified SiO2 generated in the NR latex. Scanning electron microscopy and water contact angle analyses were applied to characterize the morphology and hydrophobicity of the CSSM, respectively. The presence of aerosol SiO2 particles from PDMS and in situ modified SiO2 by OTES (MSi-O) or HDTMS (MSi-H) generated in the NR could enhance the surface roughness and hydrophobicity of the CSSM. The hydrophobic CSSM was then applied for the separation of chloroform/seawater and crude oil/seawater mixtures. A high separation efficiency (up to 99.3%) with the PDMS/NR/MSi-H CSSM was obtained and the mesh was reusable for up to 20 cycles.
Combined maternal central adiposity measures in relation to infant birth size
Authors: Lindberger Emelie , Ahlsson Fredrik , Junus Katja , Wikström Anna-Karin , Sundström Poromaa Inger
Published: January 2024

Improvement of prenatal identification of large-for-gestational-age (LGA) infants could lower the risk for adverse outcomes. Therefore, we sought to evaluate the association of a combination of maternal waist circumference (WC) and abdominal fat depths with infant birth size. A cohort study including 1240 women was performed between 2015 and 2018 at Uppsala University Hospital, Sweden. Maternal WC was measured at the first antenatal visit, and visceral (VF) and subcutaneous (SCF) fat depths by ultrasound at the second-trimester anomaly scan. Waist circumference, VF, and SCF were categorized as low or high (cut-offs WC ≥ 88 cm, VF ≥ 54 mm, SCF ≥ 21 mm). Outcomes were birth weight standard deviation score (BWSDS) and LGA (BWSDS > 90th and > 97th percentile). Secondary outcome was small-for-gestational-age (SGA, BWSDS < 10th and < 3rd percentile). Univariate analysis of variance and logistic regression analyses were performed adjusted for maternal weight, height, parity, smoking, country of birth, pregestational diabetes, and chronic hypertension. For both high and low WC, high VF was positively associated with BWSDS and LGA. There was no association with SGA. The results did not demonstrate any value of the combination of WC and fat depth measures in predicting infant birth size but suggested VF as a marker for large infants.
A twin convolutional neural network with hybrid binary optimizer for multimodal breast cancer digital image classification
Authors: Oyelade Olaide N. , Irunokhai Eric Aghiomesi , Wang Hui
Published: January 2024

There is a wide application of deep learning technique to unimodal medical image analysis with significant classification accuracy performance observed. However, real-world diagnosis of some chronic diseases such as breast cancer often require multimodal data streams with different modalities of visual and textual content. Mammography, magnetic resonance imaging (MRI) and image-guided breast biopsy represent a few of multimodal visual streams considered by physicians in isolating cases of breast cancer. Unfortunately, most studies applying deep learning techniques to solving classification problems in digital breast images have often narrowed their study to unimodal samples. This is understood considering the challenging nature of multimodal image abnormality classification where the fusion of high dimension heterogeneous features learned needs to be projected into a common representation space. This paper presents a novel deep learning approach combining a dual/twin convolutional neural network (TwinCNN) framework to address the challenge of breast cancer image classification from multi-modalities. First, modality-based feature learning was achieved by extracting both low and high levels features using the networks embedded with TwinCNN. Secondly, to address the notorious problem of high dimensionality associated with the extracted features, binary optimization method is adapted to effectively eliminate non-discriminant features in the search space. Furthermore, a novel method for feature fusion is applied to computationally leverage the ground-truth and predicted labels for each sample to enable multimodality classification. To evaluate the proposed method, digital mammography images and digital histopathology breast biopsy samples from benchmark datasets namely MIAS and BreakHis respectively. Experimental results obtained showed that the classification accuracy and area under the curve (AUC) for the single modalities yielded 0.755 and 0.861871 for histology, and 0.791 and 0.638 for mammography. Furthermore, the study investigated classification accuracy resulting from the fused feature method, and the result obtained showed that 0.977, 0.913, and 0.667 for histology, mammography, and multimodality respectively. The findings from the study confirmed that multimodal image classification based on combination of image features and predicted label improves performance. In addition, the contribution of the study shows that feature dimensionality reduction based on binary optimizer supports the elimination of non-discriminant features capable of bottle-necking the classifier.
Circulating microRNAs from plasma as preclinical biomarkers of epileptogenesis and epilepsy
Authors: Szydlowska Kinga , Bot Anna , Nizinska Karolina , Olszewski Maciej , Lukasiuk Katarzyna
Published: January 2024

Epilepsy frequently develops as a result of brain insult; however, there are no tools allowing to predict which patients suffering from trauma will eventually develop epilepsy. microRNAs are interesting candidates for biomarkers, as several of them have been described to change their levels in the brains, and in the plasma of epileptic subjects. This study was conducted to evaluate the usefulness of plasma miRNAs as epileptogenesis/epilepsy biomarkers. In our studies, we used a rat model of temporal lobe epilepsy. An epileptogenic insult was status epilepticus evoked by stimulation of the left lateral nucleus of the amygdala. Next, animals were continuously video and EEG monitored for 3 months. Blood was collected at 14, 30, 60, and 90 days after stimulation. Blood plasma was separated and miRNA levels were analyzed. We compared miRNA levels between sham-operated and stimulated animals, and between animals with high and low numbers of seizures. We propose three miRNAs that could be biomarkers of epilepsy: miR-671, miR-9a-3p and miR-7a-5p. According to us, miR-206-5p is a potential biomarker of epileptogenesis, and miR-221-3p is a potential biomarker of epilepsy severity. We think that these five miRNAs can be considered in the future as potential treatment targets.
Immune and stromal transcriptional patterns that influence the outcome of classic Hodgkin lymphoma
Authors: Menéndez Victoria , Solórzano José L. , García-Cosío Mónica , Alonso-Alonso Ruth , Rodríguez Marta , Cereceda Laura , Fernández Sara , Díaz Eva , Montalbán Carlos , Estévez Mónica , Piris Miguel A. , García Juan F.
Published: January 2024

Classic Hodgkin lymphoma (cHL) is characterized by a rich immune microenvironment as the main tumor component. It involves a broad range of cell populations, which are largely unexplored, even though they are known to be essential for growth and survival of Hodgkin and Reed–Sternberg cells. We profiled the gene expression of 25 FFPE cHL samples using NanoString technology and resolved their microenvironment compositions using cell-deconvolution tools, thereby generating patient-specific signatures. The results confirm individual immune fingerprints and recognize multiple clusters enriched in refractory patients, highlighting the relevance of: (1) the composition of immune cells and their functional status, including myeloid cell populations (M1-like, M2-like, plasmacytoid dendritic cells, myeloid-derived suppressor cells, etc.), CD4-positive T cells (exhausted, regulatory, Th17, etc.), cytotoxic CD8 T and natural killer cells; (2) the balance between inflammatory signatures (such as IL6, TNF, IFN-γ/TGF-β) and MHC-I/MHC-II molecules; and (3) several cells, pathways and genes related to the stroma and extracellular matrix remodeling. A validation model combining relevant immune and stromal signatures identifies patients with unfavorable outcomes, producing the same results in an independent cHL series. Our results reveal the heterogeneity of immune responses among patients, confirm previous findings, and identify new functional phenotypes of prognostic and predictive utility.
Indirect impacts of a highway on movement behavioral states of a threatened tortoise and implications for landscape connectivity
Authors: Harju Seth , Cambrin Scott , Berg Jodi
Published: January 2024

Roads have often been identified as barriers to the movement of free-ranging animals. However, whether restoration of landscape connectivity across roadways can mitigate barriers to movement is insufficiently understood in light of indirect effects of roads on wildlife movement. We GPS-tagged free-ranging Mojave desert tortoises (Gopherus agassizii) to quantify movement behavioral states using hidden Markov models in relation to a major highway and to document use of existing, permeable culverts. We then used the observed movement behaviors to parameterize simulations of tortoise movement to evaluate alternative culvert designs and placements for enhancing connectivity across the roadway. Tortoises were most active during mid-day, in warm temperatures, and when close to the highway. The highway affected transition probabilities between movement states, as females were more likely than males to switch to an energy-demanding traveling movement state, remain in that state, and move farther than usual within that state. In contrast, males were more likely than females to continue in the low-energy resting state when close to the highway, but if traveling, to travel farther than usual. We observed two highway crossings by a tagged tortoise, which was a higher rate of crossing than in simulated tortoises. Simulated crossing rates increased with culvert size and culvert density, and size and density appeared more important for crossing than if culverts were placed singly or in pairs. Existing culvert densities across the region appeared potentially sufficient for long-term genetic connectivity, but only if retrofitted to allow for tortoise access and passing. We concluded that existing highway traffic may indirectly depress tortoise populations adjacent to the highway, particularly via negative impacts to female movements, and that existing culverts in washes should be retrofitted to allow for periodic tortoise crossings to improve structural connectivity for occasional passage.
$$\mathscr {S}\mathscr {E}\mathscr {I}\mathscr {A}\mathscr {R}\mathscr {S}$$ model for analyzing $$\mathscr {C}\mathscr {O}\mathscr {V}\mathscr {I}\mathscr {D}$$-19 pandemic process via $$\uppsi $$-Caputo fractional derivative and numerical simulation
Authors: Mohammadaliee Behnam , Roomi Vahid , Samei Mohammad Esmael
Published: January 2024

The objective of this study is to develop the $$\mathscr {S}\mathscr {E}\mathscr {I}\mathscr {A}\mathscr {R}\mathscr {S}$$

S
E
I
A
R
S

epidemic model for $$\mathscr {C}\mathscr {O}\mathscr {V}\mathscr {I}\mathscr {D}$$

C
O
V
I
D

-$${\textbf {19}}$$
19
utilizing the $$\uppsi $$
ψ
-Caputo fractional derivative. The reproduction number ($$\breve{\mathscr {R}}_0$$

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0

) is calculated utilizing the next generation matrix method. The equilibrium points of the model are computed, and both the local and global stability of the disease-free equilibrium point are demonstrated. Sensitivity analysis is discussed to describe the importance of the parameters and to demonstrate the existence of a unique solution for the model by applying a fixed point theorem. Utilizing the fractional Euler procedure, an approximate solution to the model is obtained. To study the transmission dynamics of infection, numerical simulations are conducted by using MatLab. Both numerical methods and simulations can provide valuable insights into the behavior of the system and help in understanding the existence and properties of solutions. By placing the values $$\texttt{t}$$
t
, $$\ln (\texttt{t})$$

ln
(
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)

and $$\sqrt{\texttt{t}}$$

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instead of $$\uppsi $$
ψ
, the derivatives of the Caputo and Caputo–Hadamard and Katugampola appear, respectively, to compare the results of each with real data. Besides, these simulations specifically with different fractional orders to examine the transmission dynamics. At the end, we come to the conclusion that the simulation utilizing Caputo derivative with the order of 0.95 shows the prevalence of the disease better. Our results are new which provide a good contribution to the current research on this field of research.
Warming-induced hydrothermal anomaly over the Earth’s three Poles amplifies concurrent extremes in 2022
Authors: Zhang Jie , Chen Haishan , Fang Xinyu , Yin Zhicong , Hu Rui
Published: January 2024

Climate warming is causing an increase in the frequency and severity of heatwaves and extreme precipitation events, posing a threat to both socioeconomic stability and human lives. In 2022, five record-breaking heatwaves and floods occurred, it is suggested a new concurrent extreme feature in the study, which is linked to the three Poles warming and ice/snow melting. The independent and synergistic effect of the three Poles warming has led to the poleward movement of westerly jet streams and amplified Rossby waves, as well as the expansion of subtropical highs in both poleward and zonal directions. Consequently, these have intensified heatwaves in the mid-high latitudes and extreme precipitation events in the Asian regions, combined with a southward displacement and weakening of the inter-hemispheric Asian summer monsoon circulations, which are response to poleward of the mid-latitude and subtropical circulations and the hydrothermal effects of the three Poles. This study highlights the significance of three Poles warming in driving amplified concurrent extremes across tropical and extratropical regions, particularly in 2022. These findings provide valuable insights into the role of snow/ice melting and related hydrothermal factors in global climate predictions and disaster prevention efforts.
Cancer drug sensitivity prediction from routine histology images
Authors: Dawood Muhammad , Vu Quoc Dang , Young Lawrence S. , Branson Kim , Jones Louise , Rajpoot Nasir , Minhas Fayyaz ul Amir Afsar
Published: January 2024

Drug sensitivity prediction models can aid in personalising cancer therapy, biomarker discovery, and drug design. Such models require survival data from randomised controlled trials which can be time consuming and expensive. In this proof-of-concept study, we demonstrate for the first time that deep learning can link histological patterns in whole slide images (WSIs) of Haematoxylin & Eosin (H&E) stained breast cancer sections with drug sensitivities inferred from cell lines. We employ patient-wise drug sensitivities imputed from gene expression-based mapping of drug effects on cancer cell lines to train a deep learning model that predicts patients’ sensitivity to multiple drugs from WSIs. We show that it is possible to use routine WSIs to predict the drug sensitivity profile of a cancer patient for a number of approved and experimental drugs. We also show that the proposed approach can identify cellular and histological patterns associated with drug sensitivity profiles of cancer patients.
STEM enables mapping of single-cell and spatial transcriptomics data with transfer learning
Authors: Hao Minsheng , Luo Erpai , Chen Yixin , Wu Yanhong , Li Chen , Chen Sijie , Gao Haoxiang , Bian Haiyang , Gu Jin , Wei Lei , Zhang Xuegong
Published: January 2024

Profiling spatial variations of cellular composition and transcriptomic characteristics is important for understanding the physiology and pathology of tissues. Spatial transcriptomics (ST) data depict spatial gene expression but the currently dominating high-throughput technology is yet not at single-cell resolution. Single-cell RNA-sequencing (SC) data provide high-throughput transcriptomic information at the single-cell level but lack spatial information. Integrating these two types of data would be ideal for revealing transcriptomic landscapes at single-cell resolution. We develop the method STEM (SpaTially aware EMbedding) for this purpose. It uses deep transfer learning to encode both ST and SC data into a unified spatially aware embedding space, and then uses the embeddings to infer SC-ST mapping and predict pseudo-spatial adjacency between cells in SC data. Semi-simulation and real data experiments verify that the embeddings preserved spatial information and eliminated technical biases between SC and ST data. We apply STEM to human squamous cell carcinoma and hepatic lobule datasets to uncover the localization of rare cell types and reveal cell-type-specific gene expression variation along a spatial axis. STEM is powerful for mapping SC and ST data to build single-cell level spatial transcriptomic landscapes, and can provide mechanistic insights into the spatial heterogeneity and microenvironments of tissues.
Exploring a general multi-pronged activation strategy for natural product discovery in Actinomycetes
Authors: Tay Dillon W. P. , Tan Lee Ling , Heng Elena , Zulkarnain Nadiah , Ching Kuan Chieh , Wibowo Mario , Chin Elaine Jinfeng , Tan Zann Yi Qi , Leong Chung Yan , Ng Veronica Wee Pin , Yang Lay Kien , Seow Deborah C. S. , Lim Yi Wee , Koh Winston , Koduru Lokanand , Kanagasundaram Yoganathan , Ng Siew Bee , Lim Yee Hwee , Wong Fong Tian
Published: January 2024

Natural products possess significant therapeutic potential but remain underutilized despite advances in genomics and bioinformatics. While there are approaches to activate and upregulate natural product biosynthesis in both native and heterologous microbial strains, a comprehensive strategy to elicit production of natural products as well as a generalizable and efficient method to interrogate diverse native strains collection, remains lacking. Here, we explore a flexible and robust integrase-mediated multi-pronged activation approach to reliably perturb and globally trigger antibiotics production in actinobacteria. Across 54 actinobacterial strains, our approach yielded 124 distinct activator-strain combinations which consistently outperform wild type. Our approach expands accessible metabolite space by nearly two-fold and increases selected metabolite yields by up to >200-fold, enabling discovery of Gram-negative bioactivity in tetramic acid analogs. We envision these findings as a gateway towards a more streamlined, accelerated, and scalable strategy to unlock the full potential of Nature’s chemical repertoire.
The structure of a tetrameric septin complex reveals a hydrophobic element essential for NC-interface integrity
Authors: Grupp Benjamin , Denkhaus Lukas , Gerhardt Stefan , Vögele Matthis , Johnsson Nils , Gronemeyer Thomas
Published: January 2024

The septins of the yeast Saccharomyces cerevisiae assemble into hetero-octameric rods by alternating interactions between neighboring G-domains or N- and C-termini, respectively. These rods polymerize end to end into apolar filaments, forming a ring beneath the prospective new bud that expands during the cell cycle into an hourglass structure. The hourglass finally splits during cytokinesis into a double ring. Understanding these transitions as well as the plasticity of the higher order assemblies requires a detailed knowledge of the underlying structures. Here we present the first X-ray crystal structure of a tetrameric Shs1-Cdc12-Cdc3-Cdc10 complex at a resolution of 3.2 Å. Close inspection of the NC-interfaces of this and other septin structures reveals a conserved contact motif that is essential for NC-interface integrity of yeast and human septins in vivo and in vitro. Using the tetrameric structure in combination with AlphaFold-Multimer allowed us to propose a model of the octameric septin rod.
Atomic-scale manipulation of buried graphene–silicon carbide interface by local electric field
Authors: Kolmer Marek , Hall Joseph , Chen Shen , Roberts Samuel , Fei Zhe , Han Yong , Tringides Michael C.
Published: January 2024

Precision of scanning tunneling microscopy (STM) enables control of matter at scales of single atoms. However, transition from atomic-scale manipulation strategies to practical devices encounters fundamental problems in protection of the designer structures formed atop the surface. In this context, STM manipulation of subsurface structures on technologically relevant materials is encouraging. Here, we propose a material platform and protocols for precise manipulation of a buried graphene interface. We show that an electric field from the STM tip reversibly controls breaking and restoring of covalent bonds between the graphene buffer layer and the SiC substrate. The process involves charge redistribution at the atomically sharp interface plane under the epitaxial graphene layer(s). This buried manipulation platform is laterally defined by unit cells from the corresponding (6×6)SiC moiré lattice of the epitaxial graphene. Local and reversible electric-field-induced patterning of graphene heterostructures from the bottom interface creates an alternative architecture concept for their applications.
Metal halide perovskites for CO2 photoreduction: recent advances and future perspectives
Authors: Dong Zhongliang , Li Bowen , Zhu Yinlong , Guo Wanlin
Published: January 2024

This review presents a comprehensive overview of state-of-the-art developments in metal halide perovskite-based catalysts for photocatalytic reduction of CO2.
Temperature- and pressure-sensitive ionic conductive elastomer for respiratory monitoring and human motion sensing
Authors: Yan Kai , Chen Hua , Wang Jun , Xu Qunna , Si Yinsong , Wu Yi
Published: January 2024

An ionic conductive elastomer sensor was prepared by blending LFICE lithium salt (LiTESI) with polyurethane. The sensor has been utilized to detect body movement and breathing patterns during different physical activities.
Study on the influence of mechanism dispersion on transient recovery voltage distribution of modular DC vacuum circuit breakers
Authors: Huang Chongyang , Yin Yongshuai , Liu Shuxin , Du Hanwen , Shan Zengyu , Cao Yundong , Yang Shurui
Published: January 2024

A simulation analysis and an experiment are carried out to investigate how the gap difference between the breaks of a direct current vacuum circuit breakers with multi‐breaks (MB‐DC VCB) caused by the mechanism dispersion of the breaker influences the distribution of TRV among the breaks. An interruption model of MB‐DC VCB, combining the continuous transition model, is established to analyse the rising rate of transient recovery voltage and the dielectric strength recovery speed of the breaks for MB‐DC VCB under different gap difference conditions. Based on the experimental platform of dual break DC vacuum circuit breaker breaking, the correctness of the simulation model is verified on a DC VCB with the double‐breaks interruption experimental platform. Moreover, a model is applied to the non‐synchronous interruption simulation of a DC VCB with three‐breaks. The relationship between the TRVs of the breaks under different gap difference conditions is analysed using the comparative analysis method, obtaining the maximum gap difference at the moment of breaking failure. The results of this study show that large‐gap breaks have a higher TRV than small‐gap breaks (the fracture of the action delay module), with double fractures reaching 1.4 times and triple fractures reaching a maximum of 1.52 times; the ability of small‐gap breaks to withstand TRV is weak, giving rise to re‐breakdown or even interruption failure; as the number of fractures increases, the maximum gap difference also increases. Improving the synchronous interruption ability of the MB‐DC VCB is conducive to improving the interruption performance and interruption success rate of this type of a circuit breaker.
Issues of agricultural specialization in the Aral sea region
Authors: Abdullaev Esen , Kdirbaeva Gulan
Published: January 2024

The content of the article is aimed at reducing the economic losses caused by the Aral Sea problem by further improving the specialization of agriculture, based on the potential of the Aral Sea region. At the same time, based on the share of agriculture in GDP, it is aimed at increasing the share of agriculture in economic growth, using the existing conditions wisely. Through the specialization of agriculture, we will be able to overcome the current problems by creating an integrated system that effectively uses the available resources in the country. These insights are based on scientific evidence and statistical observations. The priority of the practical work on the Aral Sea in our country will be to improve the living standards of the population through the efficient use of inefficient land. By building agricultural specialization with modern technologies, we will be able to effectively address important issues in the Aral Sea region. The measures taken in recent years also mean that the Aral Sea issue is one of our priorities at the national level.
Examining limitations and future directions in climate change simulation models
Authors: Bozkurt Fatma , Kızıldeniz Tefide
Published: January 2024

Climate change refers to significant alterations in long-term climate conditions. If greenhouse gas emissions continue to rise, there is a high probability of exceeding the 1.5°C and 2° thresholds of global warming throughout the 21st century. This situation poses a serious threat to the agriculture sector and can lead to a decline in agricultural production and a reduction in product quality. Additionally, intensive farming practices can decrease the resilience of agriculture. This study aims to examine the effects of climate change on the agriculture sector, explain the concept of modeling and the parameters that can be measured, provide guidance on how modeling studies on alfalfa, and similar crops can be improved by identifying their shortcomings. The modeling method is used in many different fields by creating abstract representations of real-world objects or events via a mathematical equation, writing algorithm, or simulation. Parameters used in alfalfa modeling include yield, growth, carbon, water, nitrogen balance, climate effects, and other factors. However, these models have shortcomings such as the need for more comprehensive data collection and testing, the requirement for more parameter adjustments, the inability to address various crops and different growth cycles, the lack of simulation of crown and root roles in growth, sensitivity in measuring soil and input factors, limited testing and research, inaccuracies in automatic classification, the absence of growth and yield simulation models, and the lack of deep learning techniques. Addressing these shortcomings is crucial for achieving more reliable and effective results in the agricultural sector. Strengthening models and addressing these deficiencies have the potential to lead to more robust and sustainable solutions in agriculture.
Agroecological assessment of spatial variability of carbon content in the conditions of disturbed sod-podzolic soils
Authors: Morev Dmitry , Potapova Vladislava , Yaroslavtsev Alexis
Published: January 2024

Soil carbon is one of the main carbon pools of terrestrial ecosystems. The carbon of arable soils is the most labile. In this regard, rapid and accurate methods for determining soil carbon in different forms are of great interest to researchers. Therefore, in this paper we decided to conduct a comparative analysis of the results of organic carbon determination using the Walkley-Black method (colorimetric method), the Dumas dry combustion method (using the CN Vario El Cube analyzer)) and the remote method using the Valeeva approach (Valeeva, Aleksandrova, Koposov, 2016) according to the values of the red channel of the spectrum, on the images obtained using an RGB camera mounted on a DJI Phantom 4 drone. For laboratory analysis, 100 soil samples of the arable horizon were collected at regular grid points, georeferenced using RTK. The correlation between the Dumas dry combustion method and potassium dichromate oxidation was 0.24 (for n = 100, significant p=0.195), allowing comparison at the trend level. The highest correlation (R = 0.39 was observed between the data obtained using the Dumas method and the Valeeva-Alexandrova approach, indicating that it can be used to estimate soil carbon dynamics from RGB images. Correlation analysis showed relationships (R = 0.63) between total carbon and microrelief, which is reflected by the drone-derived digital elevation model.
Genomic Selection in Animal Breeding
Authors: Demircioglu Hasan Batuhan
Published: January 2024

Genomic selection endeavors to determine the reproductive values and characteristics of offspring in a given population through the utilization of high-density genetic markers. In contemporary breeding methods, classical approaches involve extended labor-intensive processes. In contrast, genomic breeding methods expedite these processes while reducing labor and time requirements. Traditional breeding management often necessitates protracted procedures to enhance the efficiency of a trait. Genomic breeding methods are economically more efficient than classical breeding techniques. With advancing technology, the identification of parental lineages for future generations occurs more rapidly compared to classical breeding methods. Various methods are available for conducting genomic selection, with marker-assisted selection being one of them. In both approaches, the utilization of selection strategies in animal husbandry plays a crucial role in determining parental lines for future generations and achieving increased productivity. The objective of this study is to compare classical selection methods with genomic selection methods.
A different perspective on agricultural products within the scope of water footprint intensity
Authors: Güney Hakan , Türkeş Selman , Sarı Bülent
Published: January 2024

Water is one of the most basic requirements for the sustainability of life on Earth. However, global climate change threatens this important resource by deeply affecting water resources and the water cycle. The sustainability of food production also depends on the proper management and protection of existing water resources. Therefore, it is important to know the amount of water required for agricultural production on a product basis and to prepare basin-based production plans taking into account water resources. The concept of water footprint (WF), which is used to express the amount of water consumed directly and indirectly in the process from the supply chain of goods and services to the end user or the extent of water pollution it causes, is presented as an important tool in water management. Nowadays, the WF calculations of agricultural products are also one of the most widely studied topics. In this study, Water Footprint Intensity is calculated for some agricultural products and the WFD of these products is evaluated through economic indicators and a different perspective is tried to be presented to the readers.
Comparison of actual evapotranspiration by the google earth engine evapotranspiration flux (EEFlux) to the METRIC model using remote sensing data and in-situ climate observations
Authors: Alsanjar Omar , Cetin Mahmut
Published: January 2024

Actual evapotranspiration (ETa) is essential data in developing water budgets and calculating irrigation water requirements in large-scale irrigation schemes. Nowadays, remote sensing (RS)-based surface energy balance models help us estimate ETa with high resolution when compared to direct methods that focus only on a single point in a field. This study aimed both at estimating ETa by Mapping EvapoTranspiration at high Resolution with Internal Calibration (METRIC) and Google Earth Engine Evapotranspiration Flux (EEFlux) platform and comparing reference evapotranspiration based on the Penman-Monteith equation (ETo) with ETa by the METRIC and EEFlux in a sub-catchment (A=9495 ha) under irrigation, located in the Lower Seyhan Plain (LSP), Turkiye in the 2020 hydrological year. For this purpose, 16 Landsat 7 and Landsat 8 images, local climatic data acquired from two meteorological stations in the catchment, and CFSv2 gridded global data were used. Results showed a good agreement between ETa-EEFlux with ETa-METRIC. Moreover, a strong correlation was found between ETo and ETa-METRIC (r=0.93 and slope close to 1 and RMSE value of 0.74 mm day-1) if compared to the relationship between ETo with ETa-EEFlux. The results show the potential of applying the METRIC model and EEFlux for mapping ETa over a large-scale irrigation scheme.
Convergence analysis of an explicit method and its random batch approximation for the McKean–Vlasov equations with non-globally Lipschitz conditions
Authors: Guo Qian , He Jie , Li Lei
Published: January 2024

In this paper, we present a numerical approach to solve the McKean–Vlasov equations, which are distribution-dependent stochastic differential equations, under some non-globally Lipschitz conditions for both the drift and diffusion coefficients. We establish a propagation of chaos result, based on which the McKean–Vlasov equation is approximated by an interacting particle system. A truncated Euler scheme is then proposed for the interacting particle system allowing for a Khasminskii- type condition on the coefficients. To reduce the computational cost, the random batch approximation proposed in [S. Jin, L. Li and J. Liu, J. Comput. Phys. 400 (2020) 108877.] is extended to the interacting particle system where the interaction could take place in the diffusion term. An almost half order of convergence is proved in Lp sense. Numerical tests are performed to verify the theoretical results.
De la Tomographie Optique par Cohérence Plein champ (FFOCT) à la Tomographie Optique par Transmission Plein Champ (FFOTT)
Authors: Mazlin Viacheslav , Alhaddad Samer , Boccara Martine , Maldiney Thomas , Touvenin Olivier , Boccara Claude
Published: January 2024

La tomographie par cohérence optique ou OCT a révolutionné le diagnostic oculaire. Nous avons proposé une variante de l’OCT, dite « plein champ » (FFOCT) dont les principales applications se sont situées en cancérologie ex et in vivo. Nous souhaitons ici introduire une nouvelle méthode de tomographie plein champ par transmission (FFOTT) et comparer les avantages et inconvénients des deux méthodes.
Measuring sales resilience value: a new approach on discount pricing strategy to develop the sales promotion program
Authors: Abdollahi Ali , Ostadi Bakhtiar , Nikbakhsh Ehsan , Kashan Ali Husseinzadeh
Published: January 2024

Economic shocks such as pandemics and natural disasters like floods and earthquakes can disrupt the market supply chain. In this study, we address the impact of both negative and positive market disruptions on product demand, and the subsequent need for adaptive strategies by marketing managers. We introduce a novel approach for measuring sales resilience value (SRV), which assists in selecting optimal discount pricing strategies during sales promotion programs. Our approach considers various states of demand disruption and is underpinned by research literature concepts and mathematical methods. A sensitivity analysis was conducted to understand the key drivers of our model, providing valuable insights for decision-making. We examined the effects of positive demand disruption on resiliency by altering the level of demand for a product of online platform in Iran during promotion while keeping other parameters constant. Our findings reveal that an increase in demand due to promotion, decreases the company’s resiliency, defined as the ratio of recovery to loss. However, by employing appropriate pricing strategies and promotion policies, companies can adapt to increased demand and improve resiliency over time through actions such as increasing production capacity. This continues until the company reaches its tolerance threshold. These results help offering significant managerial insights for effectively utilizing this concept in real-world applications.
Comparison between Off-Pump and On-Pump Beating Heart Coronary Artery Bypass Grafting
Authors: Matsuhashi Kazuki , Takami Yoshiyuki , Maekawa Atsuo , Yamana Koji , Akita Kiyotoshi , Amano Kentaro , Takagi Yasushi
Published: January 2024

Background Although coronary artery bypass grafting (CABG) is performed via three different techniques, conventional, on-pump beating heart CABG (ONBHCAB), or off-pump CABG (OPCAB), data are limited to compare ONBHCAB with OPCAB.

Methods We retrospectively investigated the postoperative cardiac biomarkers, creatine kinase-MB (CK-MB), and troponin I (cTnI), and early and late outcomes in 806 patients undergoing isolated ONBHCAB or OPCAB between February 2008 and September 2022. To eliminate the bias between different groups, propensity score matching was conducted to validate the findings.

Results After matching, the number of each study group totaled 270 patients. In both complete and matched cohorts, early outcomes, including morbidities and mortalities, were similar. However, cTnI and CK-MB levels were significantly higher after ONBHCAB than after OPCAB with median peak cTnI of 9.85 versus 4.60 ng/mL and median peak CK-MB of 48.45 versus 17.10 ng/mL in the matched cohort, which were quite low, below the threshold for values defining perioperative myocardial infarction. At follow-up of 73 ± 45 months, the overall actuarial survival rates were similar between the ONBHCAB and OPCAB patients (86 vs. 87% at 5 years and 64 vs. 68% at 10 years, respectively, in the matched cohort).

Conclusion ONBHCAB may be a comparable alternative to OPCAB with similar early and late outcomes, despite higher elevation of postoperative cardiac biomarkers. ONBHCAB provides more efficient hemodynamic support, providing a better surgical visual field, than OPCAB while reducing the risk of incomplete revascularization.
Mapping the Current Research on Mindfulness Interventions for Individuals with Cerebral Palsy: A Scoping Review
Authors: Tedeschi Roberto
Published: January 2024

Cerebral palsy (CP) is a chronic neurological disorder that can cause motor and cognitive disabilities. Mindfulness is a form of meditation that has gained attention as a potential therapeutic intervention for improving the health and well-being of patients with CP. Four databases were searched until January 2023. A scoping review was conducted to explore the role of mindfulness in the management of CP by reviewing the available scientific literature. Studies that examined the effects of mindfulness on motor function, communication, and quality of life in patients with CP were analyzed. The gray literature and reference lists of included articles were not identified. The results were presented in numerical and thematic forms. From an initial pool of 30 registered studies, only 3 met the inclusion criteria. These selected studies reported positive effects of mindfulness interventions on communication abilities and stress management in patients with CP. The available evidence suggests that mindfulness may have beneficial effects on motor function, communication, and quality of life in patients with CP. The findings of this review highlight the potential of mindfulness as a complementary therapy for improving the health and well-being of patients with CP.
Early-Onset Dystonia and Visual Impairment Preceding Epileptic Encephalopathy Associated with PIGA Gene Mutation
Authors: Franquelim Catarina , Romana Andreia , Rachão Augusto , Martins Joana Sousa , Monteiro José Paulo , Carvalho João
Published: January 2024

The association between dystonia and early-onset epileptic encephalopathy (EOEE) may have a genetic basis. Phosphatidylinositol glycan biosynthesis class A protein (PIGA) germline mutations have been described in the last decade and associated with refractory EOEEs. Dysmorphisms and visceral abnormalities have also been reported. Here, we present the case of a now 8-month-old child who was evaluated for dystonia, visual impairment, and developmental delay at 2 months of age, followed by refractory focal seizures when he was 4 months old. The remaining examination was normal, besides an accelerated linear growth. His brain magnetic resonance and an extensive metabolic investigation failed to show any abnormalities. At 7 months of age, the exome sequencing found a hemizygous PIGA pathogenic variant-c.1352T > C (p.(Ile451Thr). Seizures improved after the association of carbamazepine with levetiracetam and the beginning of the ketogenic diet. To our knowledge, this is the first time the phenotype associated with this specific mutation is described. Our patient had the singularity of manifesting with remarkable dystonia, over 2 months before the onset of seizures. We also point to the utility of the gene sequencing approach in the diagnosis of patients with dystonia and EOEEs, since identification of the genetic cause may help in patient's management and families' empowerment.
Ist die exsudative neovaskuläre AMD eine chronische Erkrankung? Analyse von Langzeitverläufen unter einer Anti-VEGF-Therapie
Authors: Gunnemann Marie-Louise , Ziegler Martin , Book Marius , Gunnemann Frederic , Rothaus Kai , Spital Georg , Gutfleisch Matthias , Lange Clemens , Lommatzsch Albrecht Peter , Pauleikhoff Daniel
Published: January 2024

Hintergrund Die Anti-VEGF-Therapie ist die Standardtherapie bei der exsudativen neovaskulären altersabhängigen Makuladegeneration (nAMD), deren Ursache die Entwicklung einer makulären Neovaskularisation (MNV) mit assoziierter Flüssigkeitsexsudation ist. Die therapeutischen Strategien (T&E oder PRN) gingen von einer narbigen Transformation der MNV aus und Exit-Strategien wurden dementsprechend formuliert. Die vorliegende Studie untersucht als Real-Life-Langzeitanalyse diese Hypothese.

Patienten 150 Augen von 97 Patienten wurden über ein mittleres Follow-up von 5,1 Jahren (1 – 14 Jahre) nach Beginn einer Anti-VEGF-Therapie zwischen 2009 und 2017 kontinuierlich bis 2022 nachbeobachtet. Behandelt wurde nach PRN-Schema analog der IVAN-Studie mit Ranibizumab, Aflibercept oder Bevacizumab. Ausgewertet wurden Länge und Intensität der Therapie.

Ergebnisse Von den 150 Augen benötigten 119 Augen (79,3%) eine fortlaufende Anti-VEGF-Therapie, während bei 18 Augen (12,0%) die Therapie aufgrund einer Stabilisierung der Situation beendet werden konnte. Bei 13 Augen (8,7%) wurde die Therapie aufgrund einer Visusverschlechterung auf ein Sehvermögen < 0,05 abgebrochen. Bei fortlaufender Therapie zeigte sich häufig eine lange Therapiedauer mit Therapieindikation beim letzten dokumentierten Arztbesuch, während eine Stabilisierung oft innerhalb der ersten 2 Behandlungsjahre erreicht wurde. Die Therapieintensität nahm vor allem nach 2013 mit Einführen der OCT-basierten Behandlungskriterien auf 7,7 – 8,0 Injektionen/Jahr zu. Die meisten Augen (74,8%) mit fortlaufender Therapie benötigten 6 – 9 Injektionen/Jahr auch noch in den letzten 3 Behandlungsjahren.

Schlussfolgerung Die Tatsache, dass in der vorliegenden Studie erneut bei der Therapie der exsudativen nAMD bei einem Großteil der Patienten (ca. 80%) eine langfristige und intensive Therapienotwendigkeit beobachtet wurde, unterstützt die Einschätzung, dass die nAMD als eine chronische Erkrankung anzusehen ist. Daher erscheint eine proaktive Behandlungsstrategie mit konsequenter Therapie bei jeglichen Aktivitätszeichen sinnvoll. Insbesondere im Hinblick auf die Gefahr des irreversiblen Visusverlusts ist zudem die Langzeitadhärenz der Patienten für ein bestmögliches langfristiges Therapieergebnis entscheidend.