bluuebunny/crossref_metadata_2025 huggingface dataset:
The Drivers and Barriers of the Solar Water Heating Entrepreneurial System: A Cost–Benefit Analysis
Authors: Yılmaz Sıdıka Ece , Yildizhan Hasan , Yıldırım Cihan , Zhao Chuang-Yao , Gomes João , Alkharusi Tarik
Published: October 2023

Sustainable development objectives place a high priority on entrepreneurship and renewable energy. Supporting entrepreneurial activities in the renewable energy industry can provide economic growth and employment to accomplish the Sustainable Development Goals Agenda 2030. Solar water heating systems can provide clear benefits for both the environment and economic growth. There is a gap in the literature regarding the study of the factors hindering or driving the development of the solar water heating system industry. This study aims to investigate the solar water heating system industry’s challenges and attempts to define the drivers to further develop the industry. Thus, solar water heating entrepreneurship parameters can be identified. Additionally, energy savings and carbon dioxide emissions were calculated for the region to raise awareness among consumers. This study used the qualitative analysis method through semi-structured interviews with 40 business owners in Adana/Turkey. The findings showed that the industry has administrative, production, political, and economic issues; there is a need for economic support and expanding education and control mechanisms. Also, the payback period is 1.63~3.27 years for a solar water heating system and this system prevents 800.75 kg of CO2 emission. The study has implications for policy-making, practice, scientific research, and the SDGs Agenda 2030.
How Does Flooding Influence Intra-Urban Mobility? The Case of Accra
Authors: Moller-Jensen Lasse , Allotey Albert N. M. , Kofie Richard Y. , Yiran Gerald A. B.
Published: October 2023

This study analyzes how daily mobility may be disrupted or constrained due to the flooding of road infrastructure. The empirical focus is Accra, Ghana, a rapidly growing African city with frequent flood events due to heavy rainfall. In the context of very scarce mobility data availability from official sources, this study proposes a novel way to utilize data from a large survey of mobility patterns conducted through in-person interviews in four peri-urban neighbourhoods. The survey targeted economically active adults and provided spatially explicit data on frequent destinations within the city when travelling in relation to income-generating activities. Using survey data on mobility patterns and detailed population data, we present a transport model with estimates of daily traffic volumes. At the city-wide scale, we propose a method for combining this transport model with maps of flood-prone locations derived from digital terrain models. At the local scale, we propose a method for analyzing the impact of flood events that restrict access to and from urban neighbourhoods. The presented results include maps of flood locations with a high impact on overall mobility, as well as maps that illustrate the spatial extent of this impact within the Accra region. At the local scale, the results illustrate the degree of potential isolation of smaller urban areas during flooding and identify the flood locations with the most significant impact on this issue. It is argued that the presented methods for identifying hotspots of flood-induced mobility disruptions may assist planners and policymakers in providing more resilient infrastructure and mitigate the adverse effects of flooding on urban transport.
Research on Real-Time Monitoring and Warning Technology for Multi-Parameter Underground Debris Flow
Authors: Zeng Qingtian , Zhu Sitao , Li Zhengrong , Wu Aixiang , Wang Meng , Su Yan , Wang Shaoyong , Qu Xiaocheng , Feng Ming
Published: October 2023

Sudden debris flows in underground mines are characterized by strong burstiness, great destructiveness, and difficult monitoring. Traditional single monitoring methods can only roughly judge the probability of underground debris flow occurrences through one-sided potential phenomena, making it difficult to accurately predict sudden underground debris flows. Therefore, effective monitoring methods can prevent or reduce waste and damage to mineral resources caused by mine debris flow disasters. This study is based on the theoretical foundations of rainfall automatic identification program, unsteady flow theory, and wavelet threshold denoising theory. It preprocesses key data such as rainfall, groundwater, and surface displacement with the aim of reducing criterion errors and improving the accuracy of determination. By utilizing the underground debris flow warning determination program, warning determination algorithm, and information management system hosted on the monitoring and warning platform, a comprehensive underground debris flow warning system is integrated. This system incorporates determining parameters such as rainfall, water inflow, groundwater level, surface subsidence, pore water pressure, surrounding rock stress, microseismic phenomena, and underground video recognition, with the innovative approach of “weather-surface-underground” multi-directional monitoring. The system was successfully installed and applied in the Pulang Copper Mine in Yunnan Province, demonstrating good application effectiveness. The results indicate that compared to traditional single monitoring methods, the multi-directional monitoring and warning system for underground debris flows has advantages such as low fault tolerance and high accuracy, making it more suitable for ensuring safe mining in mining areas.
Exploring the Interplay of the Physical Environment and Organizational Climate in Innovation
Authors: Peng Lei , Jia Ruiying
Published: October 2023

The intricate relationship between physical and social environments within organizations plays a pivotal role in shaping innovation endeavors. This paper introduces a three-dimensional framework aimed at comprehending the intricate mechanisms through which the physical and social environments synergistically drive innovation. Building on this, a systematic four-dimensional framework (communality, individuality, comfort, and health) is proposed to structure a comprehensive literature review, mapping out the intricate linkages between innovation and the physical environment. Through this extensive review, we delve into the intricate connections between the physical innovation environment and the broader innovation climate, unearthing valuable insights. Additionally, we highlight two promising directions for future research within the realm of physical environment–innovation climate interactions. Furthermore, we underscore the paramount importance of embracing an interdisciplinary approach, seamlessly blending perspectives from both the physical and social spheres to gain a holistic and nuanced understanding of the innovation landscape. This integrated viewpoint is pivotal to unraveling the multifaceted dynamics that underlie successful innovation initiatives.
Analysis of Potential Supply of Ecosystem Services in Forest Remnants through Neural Networks
Authors: Longo Regina Márcia , da Silva Alessandra Leite , Nunes Adélia N. , de Melo Conti Diego , Gomes Raissa Caroline , Sperandio Fabricio Camillo , Ribeiro Admilson Irio
Published: October 2023

Analyzing the landscape configuration factors where they are located can ensure a more accurate spatial assessment of the supply of ecosystem services. It can also show if the benefits promoted by ecosystems depend not only on the supply of these services but also on the demand, the cultural values, and the interest of the society where they are located. The present study aims to demonstrate the provision potential of regulating ecosystem services by forest remnants in the municipality of Campinas/SP, Brazil, from the analysis and weighting of geospatial indicators, considering the assumptions of supply of and demand for these ecosystem services. The potential supply of regulating ecosystem services was evaluated through the application of an artificial neural network using landscape indicators previously surveyed for the 2319 forest remnants identified in six watersheds. The findings show that the classified remnants have a “medium” to “very high” regulating potential for the provision of ecosystem services. The use of artificial intelligence fundamentals, based on artificial neural networks, proved to be quite effective, as it enables combined analysis of various indicators, analysis of spatial patterns, and the prediction of results, which could be informative guides for environmental planning and management in urban spaces.
Agriculture Risks and Opportunities in a Climate-Vulnerable Watershed in Northeastern Taiwan—The Opinions of Leisure Agriculture Operators
Authors: Chen Wan-Jiun , Jan Jihn-Fa , Chung Chih-Hsin , Liaw Shyue-Cherng
Published: October 2023

This study investigated the agriculture risks and opportunities in a fragile watershed, the Lanyang River Watershed (LRW) in Northeastern Taiwan, under the current situation of climate change. Agriculture in the LRW is a traditional sector, highly vulnerable to climate change, and is a declining economic sector due to the trend of trade liberalization of agriculture. At present, the government of Taiwan encourages local farmers to transform towards recreational farm types. Leisure agriculture operators have successfully transitioned their tilling to a business model of recreational farming. A telephone survey of leisure agriculture operators was applied with a three-stage approach to obtain their opinions. The results showed that climate change may entail risks for agriculture in watersheds. Transformation to leisure agriculture can enhance farm adaptation and increase farm income. The long-term implementation of slope- and geology-based land classification and land use planning can protect the watershed, especially from extreme weather, while enhancing water and soil conservation efforts, and bolstering climate resilience. Innovative agricultural practices offer viable solutions, including greenhouse farming for high-economic-value crops, leisure agriculture, organic farming, and ecotourism. These strategies can rejuvenate the LRW’s agriculture industry, foster ecological tourism, and provide opportunities for traditional farmers to thrive in this highly climate-fragile area. The implications of this case study are that appropriate responses can improve local climate resilience, and that correspondingly well-designed adaptation measures can transform threats and risks into new opportunities.
The Environmental Impacts of Automated Vehicles on Parking: A Systematic Review
Authors: Kong You , Ou Jihong , Chen Longfei , Yang Fengchun , Yu Bo
Published: October 2023

Automated Vehicles (AVs) can drop off passengers at predetermined destinations and relocate to less expensive, remote parking facilities, which offers the potential to repurpose valuable urban land near activity centers for alternative uses beyond vehicle storage. While some researchers believe AVs are the core element to solving parking problems, relieving urban land use, and enabling low-emission travel, others contend that AVs could incentivize increased Vehicles Miles Traveled (VMT) and exacerbate congestion. To bridge these disparate perspectives, this study endeavors to elucidate the environmental ramifications of AVs on parking through a comprehensive literature review. Based on an initial sample of 299 retrieved papers, 52 studies were selected as the result of the selection criteria detailed in the paper. The selected papers were categorized into five gradual parts to answer the raised research questions. As a principal finding of this study, our research provides city planners, traffic operators, and scholars with full-picture insights and trustworthy guidance, emphasizing the pivotal role of AVs in deciphering the sustainable impact on the urban environment.
Multi-Objective Considered Process Parameter Optimization of Welding Robots Based on Small Sample Size Dataset
Authors: Yan Jihong , Zhang Mingyang , Xu Yuchun
Published: October 2023

The welding process is characterized by its high energy density, making it imperative to optimize the energy consumption of welding robots without compromising the quality and efficiency of the welding process for their sustainable development. The above evaluation objectives in a particular welding situation are mostly influenced by the welding process parameters. Although numerical analysis and simulation methods have demonstrated their viability in optimizing process parameters, there are still limitations in terms of modeling accuracy and efficiency. This paper presented a framework for optimizing process parameters of welding robots in industry settings, where data augmentation was applied to expand sample size, auto machine learning theory was incorporated to quantify reflections from process parameters to evaluation objectives, and the enhanced non-dominated sorting algorithm was employed to identify an optimal solution by balancing these objectives. Additionally, an experiment using Q235 as welding plates was designed and conducted on a welding platform, and the findings indicated that the prediction accuracy on different objectives obtained by the enlarged dataset through ensembled models all exceeded 95%. It is proven that the proposed methods enabled the efficient and optimal determination of parameter instructions for welding scenarios and exhibited superior performance compared with other optimization methods in terms of model correctness, modeling efficiency, and method applicability.
On Geometric Interpretations of Euler’s Substitutions
Authors: Cieśliński Jan L. , Jurgielewicz Maciej
Published: October 2023

We consider a classical case of integrals containing an irrational integrand in the form of a square root of a quadratic polynomial. It is known that such “irrational integrals” can be expressed in terms of elementary functions by one of three of Euler’s substitutions. It is less well known that the Euler substitutions have a geometric interpretation. In the framework of this interpretation, one can see that the number 3 is not the most suitable. We show that it is natural to introduce a fourth Euler substitution. In his original treatise, Leonhard Euler used two substitutions which are sufficient to cover all cases.
\({\ell_0}\) Optimization with Robust Non-Oracular Quantum Search
Authors: Zhang  Tianyi , Ke Yuan
Published: October 2023

In this article, we introduce an innovative hybrid quantum search algorithm, the Robust Non-oracle Quantum Search (RNQS), which is specifically designed to efficiently identify the minimum value within a large set of random numbers. Distinct from the Grover’s algorithm, the proposed RNQS algorithm circumvents the need for an oracle function that describes the true solution state, a feature often impractical for data science applications. Building on existing non-oracular quantum search algorithms, RNQS enhances robustness while substantially reducing running time. The superior properties of RNQS have been demonstrated through careful analysis and extensive empirical experiments. Our findings underscore the potential of the RNQS algorithm as an effective and efficient solution to combinatorial optimization problems in the realm of quantum computing.
A Review on the Use of Imaging Biomarkers in Oncology Clinical Trials: Quality Assurance Strategies for Technical Validation
Authors: Chauvie Stephane , Mazzoni Lorenzo Nicola , O’Doherty Jim
Published: October 2023

Imaging biomarkers (IBs) have been proposed in medical literature that exploit images in a quantitative way, going beyond the visual assessment by an imaging physician. These IBs can be used in the diagnosis, prognosis, and response assessment of several pathologies and are very often used for patient management pathways. In this respect, IBs to be used in clinical practice and clinical trials have a requirement to be precise, accurate, and reproducible. Due to limitations in imaging technology, an error can be associated with their value when considering the entire imaging chain, from data acquisition to data reconstruction and subsequent analysis. From this point of view, the use of IBs in clinical trials requires a broadening of the concept of quality assurance and this can be a challenge for the responsible medical physics experts (MPEs). Within this manuscript, we describe the concept of an IB, examine some examples of IBs currently employed in clinical practice/clinical trials and analyze the procedure that should be carried out to achieve better accuracy and reproducibility in their use. We anticipate that this narrative review, written by the components of the EFOMP working group on “the role of the MPEs in clinical trials”-imaging sub-group, can represent a valid reference material for MPEs approaching the subject.
Clinical Applicability of Electrical Impedance Tomography in Patient-Tailored Ventilation: A Narrative Review
Authors: Heines Serge J. H. , Becher Tobias H. , van der Horst Iwan C. C. , Bergmans Dennis C. J. J.
Published: October 2023

Electrical Impedance Tomography (EIT) is a non-invasive bedside imaging technique that provides real-time lung ventilation information on critically ill patients. EIT can potentially become a valuable tool for optimising mechanical ventilation, especially in patients with acute respiratory distress syndrome (ARDS). In addition, EIT has been shown to improve the understanding of ventilation distribution and lung aeration, which can help tailor ventilatory strategies according to patient needs. Evidence from critically ill patients shows that EIT can reduce the duration of mechanical ventilation and prevent lung injury due to overdistension or collapse. EIT can also identify the presence of lung collapse or recruitment during a recruitment manoeuvre, which may guide further therapy. Despite its potential benefits, EIT has not yet been widely used in clinical practice. This may, in part, be due to the challenges associated with its implementation, including the need for specialised equipment and trained personnel and further validation of its usefulness in clinical settings. Nevertheless, ongoing research focuses on improving mechanical ventilation and clinical outcomes in critically ill patients.
Head and Neck Cancer Segmentation in FDG PET Images: Performance Comparison of Convolutional Neural Networks and Vision Transformers
Authors: Xiong Xiaofan , Smith Brian J. , Graves Stephen A. , Graham Michael M. , Buatti John M. , Beichel Reinhard R.
Published: October 2023

Convolutional neural networks (CNNs) have a proven track record in medical image segmentation. Recently, Vision Transformers were introduced and are gaining popularity for many computer vision applications, including object detection, classification, and segmentation. Machine learning algorithms such as CNNs or Transformers are subject to an inductive bias, which can have a significant impact on the performance of machine learning models. This is especially relevant for medical image segmentation applications where limited training data are available, and a model’s inductive bias should help it to generalize well. In this work, we quantitatively assess the performance of two CNN-based networks (U-Net and U-Net-CBAM) and three popular Transformer-based segmentation network architectures (UNETR, TransBTS, and VT-UNet) in the context of HNC lesion segmentation in volumetric [F-18] fluorodeoxyglucose (FDG) PET scans. For performance assessment, 272 FDG PET-CT scans of a clinical trial (ACRIN 6685) were utilized, which includes a total of 650 lesions (primary: 272 and secondary: 378). The image data used are highly diverse and representative for clinical use. For performance analysis, several error metrics were utilized. The achieved Dice coefficient ranged from 0.833 to 0.809 with the best performance being achieved by CNN-based approaches. U-Net-CBAM, which utilizes spatial and channel attention, showed several advantages for smaller lesions compared to the standard U-Net. Furthermore, our results provide some insight regarding the image features relevant for this specific segmentation application. In addition, results highlight the need to utilize primary as well as secondary lesions to derive clinically relevant segmentation performance estimates avoiding biases.
Evaluation of a Deep Learning Reconstruction for High-Quality T2-Weighted Breast Magnetic Resonance Imaging
Authors: Allen Timothy J. , Henze Bancroft Leah C. , Unal Orhan , Estkowski Lloyd D. , Cashen Ty A. , Korosec Frank , Strigel Roberta M. , Kelcz Frederick , Fowler Amy M. , Gegios Alison , Thai Janice , Lebel R. Marc , Holmes James H.
Published: October 2023

Deep learning (DL) reconstruction techniques to improve MR image quality are becoming commercially available with the hope that they will be applicable to multiple imaging application sites and acquisition protocols. However, before clinical implementation, these methods must be validated for specific use cases. In this work, the quality of standard-of-care (SOC) T2w and a high-spatial-resolution (HR) imaging of the breast were assessed both with and without prototype DL reconstruction. Studies were performed using data collected from phantoms, 20 retrospectively collected SOC patient exams, and 56 prospectively acquired SOC and HR patient exams. Image quality was quantitatively assessed via signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and edge sharpness. Qualitatively, all in vivo images were scored by either two or four radiologist readers using 5-point Likert scales in the following categories: artifacts, perceived sharpness, perceived SNR, and overall quality. Differences in reader scores were tested for significance. Reader preference and perception of signal intensity changes were also assessed. Application of the DL resulted in higher average SNR (1.2–2.8 times), CNR (1.0–1.8 times), and image sharpness (1.2–1.7 times). Qualitatively, the SOC acquisition with DL resulted in significantly improved image quality scores in all categories compared to non-DL images. HR acquisition with DL significantly increased SNR, sharpness, and overall quality compared to both the non-DL SOC and the non-DL HR images. The acquisition time for the HR data only required a 20% increase compared to the SOC acquisition and readers typically preferred DL images over non-DL counterparts. Overall, the DL reconstruction demonstrated improved T2w image quality in clinical breast MRI.
Biliary Leak after Pediatric Liver Transplantation Treated by Percutaneous Transhepatic Biliary Drainage—A Case Series
Authors: Doppler Michael , Fürnstahl Christin , Hammer Simone , Melter Michael , Verloh Niklas , Schlitt Hans Jürgen , Uller Wibke
Published: October 2023

Background: Biliary leaks are a severe complication after pediatric liver transplantation (pLT), and successful management is challenging. Objectives: The aim of this case series was to assess the outcome of percutaneous transhepatic biliary drainage (PTBD) in children with bile leaks following pLT. The necessity of additional percutaneous bilioma drainage and laboratory changes during therapy and follow-up was documented. Material and Methods: All children who underwent PTBD for biliary leak following pLT were included in this consecutive retrospective single-center study and analyzed regarding site of leak, management of additional bilioma, treatment response, and patient and transplant survival. The courses of inflammation, cholestasis parameters, and liver enzymes were retrospectively reviewed. Results: Ten children underwent PTBD treatment for biliary leak after pLT. Seven patients presented with leakage at the hepaticojejunostomy, two with leakage at the choledocho-choledochostomy and one with a bile leak because of an overlooked segmental bile duct. In terms of the mean, the PTBD treatment started 40.3 ± 31.7 days after pLT. The mean duration of PTBD treatment was 109.7 ± 103.6 days. Additional percutaneous bilioma drainage was required in eight cases. Bile leak treatment was successful in all cases, and no complications occurred. The patient and transplant survival rate was 100%. CRP serum level, leukocyte count, gamma-glutamyl transferase (GGT), and total and direct bilirubin level decreased significantly during treatment with a very strong effect size. Additionally, the gamma-glutamyl transferase level showed a statistically significant reduction during follow-up. Conclusions: PTBD is a very successful strategy for bile leak therapy after pLT.
Case Study of Diesters of o-Phthalic Acid in Surface Waters with Background Levels of Pollution
Authors: Gorshkov Alexander , Grigoryeva Tatyana , Bukin Yurij , Kuzmin Anton
Published: October 2023

Lake Baikal was studied as a model for elucidating the general pattern of o-phthalic acid diester (PAE) distributions in surface waters with background pollution levels. The influence of factors including congeners, concentrations, sampling points, seasons, years, and potential sources was considered and the environmental risk for various hydrobionts was established. Priority PAEs in Baikal waters are represented by dimethyl phthalate (DMP), diethyl phthalates (DEP), di-n-butyl phthalate (DnBP) and di-(2-ethylhexyl)phthalate (DEHP). Statistically valuable average concentrations and ranges for DMP, DEP, DnBP, and DEHP were 0.02 (0.01–0.02), 0.07 (0.06–0.09), 0.55 (0.47–0.66), and 0.30 (0.26–0.34) µg/L, respectively. The main factors determining PAE concentrations were the year and season of sampling, whereas sampling points were not among the factors influencing PAE levels. The distribution of PAEs in the water body was characterized by (i) an even distribution of minor hydrophilic DMP and DEP congeners in the whole water body, (ii) a maximum concentration of hydrophobic DnBP and DEHP congeners in the upper and near-bottom layers of the water column, and (iii) a low concentration of hydrophobic congeners in the near-shore area. The main PAE source was found to be the atmospheric transfer of polluted air masses, while the supply of PAEs from coastal sources to the pelagic zone was low. The contribution of biogenic sources to the background level of PAEs in the surface waters of Lake Baikal was established. The ecological risk of the background concentration level of PAEs for Lake Baikal biota was estimated. It was found that (i) DMP and DEP congeners do not represent a risk, or represent a very low risk, (ii) the concentration levels of dominant DnBP and DEHP congeners represent a low risk for crustaceans and fishes but (iii) a rather high risk for algae at a DEHP concentration of 0.30 µg/L.
Reply to Taylor et al. Comment on “Manna et al. SARS-CoV-2 Inactivation in Aerosol by Means of Radiated Microwaves. Viruses 2023, 15, 1443”
Authors: Manna Antonio , De Forni Davide , Bartocci Marco , Pasculli Nicola , Poddesu Barbara , Lista Florigio , De Santis Riccardo , Amatore Donatella , Grilli Giorgia , Molinari Filippo , Sangiovanni Vincentelli Alberto , Lori Franco
Published: October 2023

SARS-CoV-2 is inactivated in aerosol (its primary mode of transmission) by means of radiated microwaves at frequencies that have been experimentally determined. Such frequencies are best predicted by the mathematical model suggested by Taylor, Margueritat and Saviot. The alignment between such mathematical prediction and the outcomes of our experiments serves to reinforce the efficacy of the radiated microwave technology and its promise in mitigating the transmission of SARS-CoV-2 in its naturally airborne state.
Evaluation of Direct Detection Protocols for Poliovirus from Stool Samples of Acute Flaccid Paralysis Patients
Authors: Ueno Minami Kikuchi , Kitamura Kouichi , Nishimura Yorihiro , Arita Minetaro
Published: October 2023

Polio surveillance in the Global Polio Eradication Initiative has been conducted with virus isolation from stool samples of acute flaccid paralysis (AFP) cases. Under the current biorisk management/regulations, challenges arise in the timelines of the report, sensitivity of the test and containment of poliovirus (PV) isolates. In the present study, we evaluated protocols of previously reported direct detection (DD) methods targeting the VP1 or VP4–VP2 regions of the PV genome in terms of sensitivity and sequencability. An optimized protocol targeting the entire-capsid region for the VP1 sequencing showed a high sensitivity (limit of detection = 82 copies of PV genome) with a simpler and faster reaction than reported ones (i.e., with the addition of all the primers at the start of the reaction, the RT-PCR reaction finishes within 2.5 h). The DD methods targeting the VP1 region detected PV in 60 to 80% of PV-positive stool samples from AFP cases; however, minor populations of PV strains in the samples with virus mixtures were missed by the methods. Sequencability of the DD methods was primarily determined by the efficiency of the PCRs for both Sanger and nanopore sequencing. The DD method targeting the VP4–VP2 region showed higher sensitivity than that targeting the VP1 region (limit of detection = 25 copies of PV genome) and successfully detected PV from all the stool samples examined. These results suggest that DD methods are effective for the detection of PV and that further improvement of the sensitivity is essential to serve as an alternative to the current polio surveillance algorithm.
Ovarian Dynamics and Changes in Estradiol-17β and Progesterone Relationship with Standing Estrus, Preovulatory Follicles, and Ovulation Using Single Prostaglandin F2α Injection in Barbari Goats
Authors: Sohail Tariq , Farhab Muhammad , Zhang Liuming , Kang Yan , Sun Xiaomei , Ji Dejun , Li Yongjun
Published: October 2023

The purpose of the present research was to define ovarian follicular dynamics and plasma endocrine profiles in response to a single PGF2α injection, administered indiscriminately during the breeding season of Barbari goats. Ovarian dynamics were observed at every 12 h interval by using B mode ultrasonography, blood samples for hormonal analysis such as estradiol 17β and progesterone were collected at every 12 h interval, and bucks with aprons were used to identify standing estrus at every 6 h interval. Relative to PGF2α, the start of standing estrus and ovulation differ (p < 0.05) between early- (n = 7), intermediate- (n = 6), and late-responding (n = 6) goats. The highest plasma level of estradiol 17β was detected 12 h prior to ovulation. The average diameter of the ovulatory follicle and length of standing estrus were comparable (p > 0.05) between the goats. The corpus luteum degenerated more quickly (p < 0.05) in early- than intermediate- and late-responding goats. Dominant follicle diameter and estradiol 17β concentration also differ (p < 0.05) among groups. Although the plasma level of progesterone did not vary (p = 0.065), the variation in progesterone concentration with time differed (p < 0.05) amongst the goats. As a result, this research indirectly reveals that the beginning of standing estrus, end of estrus, and ovulation after PGF2α might fluctuate in Barbari goats because of follicular and hormonal dynamics during the luteal phase.
Linkages between Meteorological and Hydrological Drought in the Jinsha River Basin under a Changing Environment
Authors: Zhang Lu , Zhang Zengxin , Peng Zhenhua , Xu Yang , Zhang Ying , Mao Jingqiao
Published: October 2023

The Jinsha River basin (JRB), known as China’s largest hydropower base, has been facing a surge in hydrological drought occurrences in the past several years. This study used the drought index model and soil and water assessment tool (SWAT) hydrological model to uncover the linkages between meteorological and hydrological drought using long-term datasets in the JRB. The results revealed that: (1) Over the past six decades, the JRB has experienced recurrent meteorological droughts, with the upper reaches being the most affected, accounting for a frequency of 17.5%. However, the frequency of drought in the middle and lower reaches has shown a marked increase in the last 15 years. (2) The frequency of hydrological drought in the JRB has been on the rise over the past six decades, with a particularly notable increase observed in the last two decades. Furthermore, a noticeable upward trend has been observed in the duration of these hydrological droughts. (3) The propagation durations from meteorological drought to hydrological drought exhibited noticeable seasonal differences in the JRB. The transmission duration during the flood season was shorter, whereas in the dry season, it was more protracted. Additionally, the connection between meteorological drought and hydrological drought demonstrates a weakening trend. The findings of this study hold significant implications for crafting an efficient reservoir dispatching strategy to safeguard the water security of the JRB.
Analysis of Variation Trend and Driving Factors of Baseflow in Typical Yellow River Basins
Authors: Quan Liyu , Liu Chengshuai , Niu Chaojie , Zhao Dong , Luo Qingyuan , Xu Yingying , Zhao Chenchen , Liu Shangbin , Hu Caihong
Published: October 2023

Baseflow is a stable part of streamflow and the main component of streamflow during the dry season. Baseflow plays an important role in the water cycle, and in ecological environment protection of the Yellow River basin (YRB). Taking the Zuli, Kuye, and Tuwei basins, and the Jingle sub-basin as examples, the baseflow was separated using a recursive digital filtering method. The intra-annual, inter-annual, and chronological characteristics of baseflow and the baseflow index (BFI) were analyzed, and driving factors were analyzed from the perspective of climate-change and human-impact factors. The results showed that: (1) The annual baseflow of the basins mainly declined, trending downward in all four test basins, while the BFI increased in two of the basins and remained nearly constant in the other two basins; however, the distributions of baseflow and the BFI were more uniform. (2) The intra-annual patterns for baseflow and the BFI showed changes between earlier and later periods. (3) Precipitation and soil and water conservation measures were the primary driving forces of baseflow change in the basins. The influence of the former weakened while the latter strengthened, and coal mining in the Kuye River and Tuwei River basins also influenced baseflow significantly. (4) When the normalized difference vegetation index (NDVI) < 0.375, the BFI of test watersheds gradually decreased with the increase in the NDVI. When 0.375 < NDVI < 0.65, the BFI of the basins gradually increased with the increase in the NDVI and the underlying surface continued to improve. When NDVI > 0.65, the increase rate of the BFI decreased and the soil and water conservation capacity of the underlying surface tended to be stable.
RLNformer: A Rainfall Levels Nowcasting Model Based on Conv1D_Transformer for the Northern Xinjiang Area of China
Authors: Liu Yulong , Liu Shuxian , Chen Juepu
Published: October 2023

Accurate precipitation forecasting is of great significance to social life and economic activities. Due to the influence of various factors such as topography, climate, and altitude, the precipitation in semi-arid and arid areas shows the characteristics of large fluctuation, short duration, and low probability of occurrence. Therefore, it is highly challenging to accurately predict precipitation in the northern Xinjiang area of China, which is located in the semi-arid and arid climate region. In this study, six meteorological stations in the northern Xinjiang area were selected as the research area. Due to the high volatility of rainfall in this area, the rainfall was divided into four levels, namely, “no rain”, “light rain”, “moderate rain”, and “heavy rain and above”, for rainfall level prediction. In order to improve the prediction performance, this study proposed a rainfall levels nowcasting model based on Conv1D_Transformer (RLNformer). Firstly, the maximum information coefficient (MIC) method was used for feature selection and sliding the data, that is, the data of the first 24 h were used to predict the rainfall levels in the next 3 h. Then, the Conv1D layer was used to replace the word-embedding layer of the transformer, enabling it to extract the relationships between features of time series data and allowing multi-head attention to better capture contextual information in the input sequence. Additionally, a normalization layer was placed before the multi-head attention layer to ensure that the input data had an appropriate scale and normalization, thereby reducing the sensitivity of the model to the distribution of input data and helping to improve model performance. To verify the effectiveness and generalization of the proposed model, the same experiments were conducted on the Indian public dataset, and seven models were selected as benchmark models. Compared with the benchmark models, RLNformer achieved the highest accuracy on both datasets, which were 96.41% and 88.95%, respectively. It also had higher accuracy in the prediction of each category, especially the minority category, which has certain reference significance and practical value.
Assessing Water Resource Carrying Capacity and Sustainability in the Cele–Yutian Oasis (China): A TOPSIS–Markov Model Analysis
Authors: Jia Guangwei , Li Sheng , Jie Feilong , Ge Yanyan , Liu Na , Liang Fuli
Published: October 2023

This study employs the Driving Force–Pressure–State–Response (DPSR) framework to establish an evaluation index system for the water resource carrying capacity (WRCC) in the Cele–Yutian Oasis (China). Utilizing the TOPSIS and obstacle degree models, we analyze the trends in the WRCC and its main hindrance factors in the Cele–Yutian Oasis from 2005 to 2020. Additionally, we employ the Markov model to investigate the dynamic changes in the land use types. The findings reveal that the most unfavorable WRCC status occurred in 2007, with a Grade IV rating (a mild overload). By 2020, the WRCC improved to a Grade III rating (critical), indicating a positive trajectory. However, persistent challenges for water resources remain, with a prolonged critical state. Over the past 15 years, the grassland area has decreased by 15.18%, and the forest area has decreased by 50%. The dynamic degree of grassland, forests, and water bodies is negative, signifying shifts to other land types, with water bodies undergoing the most significant change at −10.16%. Based on the outcomes of these two models, we propose regionally tailored measures to support sustainable development. These research results provide a scientific foundation for optimal water resource allocation and sustainable development in the Cele–Yutian Oasis Economic Belt.
Three-Dimensional Numerical Analysis and Operational Optimization of High-Efficiency Sedimentation Tank
Authors: Ye Zhian , Kang Shaoxin , Wang Zhengjiang , Jiang Qi , Zhang Jiangtao , Zheng Bin , Wang Jinlei
Published: October 2023

The high-efficiency sedimentation tank has a wide range of application prospects in industrial wastewater treatment due to its small footprint, strong resistance to shock loads, and high efficiency. However, the complex flow field distribution inside significantly affects the treatment performance of the high-efficiency tank. In this study, a three-dimensional geometric model of the high-efficiency sedimentation tank was constructed based on an engineering prototype. The corresponding solid–liquid two-phase, whole-process computational fluid dynamics (CFD) model for the high-efficiency sedimentation tank was established using the realizable k-ε turbulent model and the multiple reference frame (MRF) method. The internal structures of the flocculation zone, plug-flow zone, and clarification zone were optimized, and then the influence of operational process conditions on the flocculation treatment performance was investigated. The results indicate that, for the given engineering model, the average turbulent kinetic energy k in the flocculation zone exhibits a trend that initially increases and then decreases with the increase in the diameter and height of the draft tube. The optimal hydraulic conditions for the flocculation zone are achieved when the diameter of the draft tube is 2.5 m and the height is 3.5 m. The average turbulent kinetic energy dissipation rate in the plug-flow/clarification zone tends to decrease first and then increase as the height of the water tunnel and water-retaining weir increases. The optimal hydraulic conditions for the plug-flow and clarification zones are achieved when the height of the water tunnel is 1.0 m and the height of the water-retaining weir is 1.6 m. Under optimal operating conditions (dosage of dense media particles: 40 mg/L, stirring rate: 30 rpm, and inlet velocity: 0.72 m/s), satisfactory overall hydraulic conditions can be achieved throughout the entire high-efficiency sedimentation tank. Comparisons between a high-efficiency settling tank and a conventional clarifier for the treatment of circulating water sewage in a practical implementation reveals that the ballasted high-efficiency settling tank has advantages in terms of high hydraulic loading, high removal efficiency of hardness, small footprint, and low doses of flocculant. This research will provide reference values for the design and operation optimization of high-efficiency sedimentation tanks.
PERLINDUNGAN TERHADAP LESSEE USAHA DALAM PERJANJIAN SEWA GUNA SEBAGAI KONTRAK BAKU
Authors: Sudjana Sudjana -
Published: October 2023

This study aims to determine the clarity of existence (leasing) in agreement and leasing law in the perspective of standard agreements.The method of approach is juridical normative and  the data is analyzed in a qualitative normative way to produce descriptive data based on the study of statutory norms.The results of the study show that leasing in treaty law has 2 (two) financing categories, namely finance lease (lease with option rights) and operating lease (lease without option rights). In contract law, the operating lease has the aspect of a lease agreement while the finance lease is more in line with the aspect of buying and selling, but each of these aspects compared to the financing category still has a difference. Whereas leasing in the standard agreement perspective applies in accordance with freedom of contract vide Article 1320 jo Article 1338 of the Civil Code as long as it does not lead to eliminating the responsibility of the business actor (exenorasi classula), but considering the lease agreement unilaterally determined by the lessor, the position of the lessee is still weak legal protection through legal action that can be carried out, for example filing a claim for compensation, costs and interest
PELINDUNGAN HUKUM MEREK PADA DEEP LINKING DI INDONESIA
Authors: Dharmawan Ananda Fersa
Published: October 2023

Permasalahan seputar praktik deep linking sebagai pelanggaran merek menunjukkan transformasi baru dalam bentuk perbuatan pelanggaran merek secara digital. Pelindungan hukum terhadap bentuk baru pelanggaran merek secara digital sangat diperlukan dalam rangka melindungi merek sebagai hak kekayaan intelektual di era TIK. Metode pendekatan yang digunakan dalam penelitian ini adalah yuridis normatif dengan menggunakan data sekunder yang berupa bahan pustaka peraturan perundang-undangan, buku dan artikel yang terkait dengan deep linking dan merek. Dari kesimpulan yang didapat melalui analisis dalam artikel ini dapat disimpulkan bahwa teori dan asas hukum yang digunakan dalam melandasi pembentukan hukum pelindungan merek dari deep linking sebagai pelanggaran merek dalam internet antara lain adalah teori pelindungan merek di era TIKteori hukum pembangunan dan teori analisis ekonomi terhadap hukum (economic analysis of law). Asas yang dapat mendasari hukum pelindungan merek dari deep linking antara lain asas Droit de Suite dan asas Itikad Baik. Sebagai dasar hukum gugatan perdata dan penuntutan pidana atas deep linking terhadap merek sekarang ini maka dapat digunakan pasal-pasal yang terdapat dalam Undang-Undang ITE karena Undang-Undang Nomor 20 Tahun 2016 tentang Merek dan Indikasi Geografis belum mengatur tentang deep linking.
KADIN MERKEZLİ BAKIMIN UYGULANMASINI KOLAYLAŞTIRAN DÜNYA SAĞLIK ÖRGÜTÜ ÖNERİSİ BİR ARAÇ: DOĞUM BAKIM KILAVUZU
Authors: CEYLAN Sinem , BULUT Şeydanur , KARAHAN Nazan
Published: October 2023

Kadın merkezli bakım, doğum öncesi, doğum ve doğum sonu annelik hizmetlerinde bir kalite göstergesi olmakla birlikte çok boyutlu ve holistik perspektifi içeren bir kavramdır. Kadın merkezli bakımla, pozitif doğum deneyimi oluşturmak için travay süreci ve doğumda bakımın kalitesinin bütünsel olarak ve insan haklarını gözeterek nasıl en uygun hale getirilebileceği Dünya Sağlık Örgütü tarafından yayınlanan kılavuzda belirtilmiştir. Dünya Sağlık Örgütü, bu kılavuzda yer alan önerilerin etkin bir şekilde uygulanabilmesi için halen kullanılmakta olan partografı yenileyerek, “Doğum Bakım Kılavuzu’nu oluşturmuştur. Yedi bölümden oluşan Doğum Bakım Kılavuzu, sağlık profesyonellerinin karar alma sürecini standardize ederek, kadın merkezli bakımı teşvik etmeyi amaçlamaktadır. Doğum Bakım Kılavuzu, doğum eylemi sırasında kadının ve fetüsün güvenliğini sağlamaya, gereksiz müdahalelerden kaçınmaya ve destekleyici bakım sunmaya özel vurgu yaparak, kanıta dayalı bakım için kaynak oluşturmaktadır. Bu derlemede, Doğum Bakım Kılavuzunun partograf ile karşılaştırmalı olarak nasıl kullanılacağının açıklanması amaçlanmıştır.
Spreadable Magnetic Soft Robots with On-Demand Hardening
Authors: Xu Zichen , Chen Yuanhe , Xu Qingsong
Published: October 2023

Magnetically actuated mobile robots demonstrate attractive advantages in various medical applications due to their wireless and programmable executions with tiny sizes. Confronted with complex application scenarios, however, it requires more flexible and adaptive deployment and utilization methods to fully exploit the functionalities brought by magnetic robots. Herein, we report a design and utilization strategy of magnetic soft robots using a mixture of magnetic particles and non-Newtonian fluidic soft materials to produce programmable, hardened, adhesive, reconfigurable soft robots. For deployment, their ultrasoft structure and adhesion enable them to be spread on various surfaces, achieving magnetic actuation empowerment. The reported technology can potentially improve the functionality of robotic end-effectors and functional surfaces. Experimental results demonstrate that the proposed robots could help to grasp and actuate objects 300 times heavier than their weight. Furthermore, it is the first time we have enhanced the stiffness of mechanical structures for these soft materials by on-demand programmable hardening, enabling the robots to maximize force outputs. These findings offer a promising path to understanding, designing, and leveraging magnetic robots for more powerful applications.