Demography and Socio-Economic Aspects on Irrigated Smallholder Agricultural Enterprises and Their Association with the Cultivation of Maize (Zea mays L.) as a Selected Field Crop

The purpose of this study is to correlate demography and socio-economic aspects at Irrigated Smallholder Agricultural Enterprises and their association with the Cultivation of Maize in order to determine its positive impacts at irrigated smallholders’ agricultural entrepreneurs’ household. Chi-square test was used as descriptive analysis method. The Fischer Exact tests were employed to test demography (gender, age, education, and income) in winter and summer production season of irrigated smallholder agricultural enterprises and their association with the cultivation of selected field crop (i.e. maize). The results show that gender results were not being statistically significant, as measured by the Phi measure of effect size, φ = 0.149, p = 0.011, and φ = 0.05, p = 0.392 in summer. As far as age is concern, it appears to be a statistically significant association between cultivating maize and age in winter, φ = 0.046, p = 0.730 in winter and φ = 0.172, p = 0.013. Education winter result not being statistically significant, the effect size showed a weak association, as measured by the Phi measure of effect size, φ = 0.112, p = 0.305 and φ = 0.035, p = 0.948 in summer. Income result not being statistically significant, as measured by the Phi measure of effect size, φ = 0.049, p = 0.399 and φ = 0.081, p = 0.166 in summer. In conclusion, the study shows that the development of best management practices must be based on a comprehensive analysis of the livelihoods and irrigated smallholder agricultural enterprise farming styles of participating irrigated smallholder agricultural entrepreneurs.

Case Retrieval Strategy of Turning Process Based on Grey Relational Analysis

To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform,a case-based reasoning framework is proposed.Specifically,a Hamming distance and Euclidean distance combined method is designed to measure the similarity of case features which have both numeric and category properties.In addition,AHP(Analytic Hierarchy Process)and entropy weight method are integrated to provide features weight,where both user preferences and comprehensive impact of the index have been concerned.Grey relation analysis is used to obtain the similarity of a new problem and alternative cases.Finally,a platform is also developed on Visual Studio 2015,and a case study is demonstrated to verify the practicality and efficiency of the proposed method.This method can obtain cutting parameters which is suitable without iterative calculation.Compared with the traditional PSO(Particle swarm optimization algorithm)and GA(Genetic algorithm),it can obtain faster response speed.This method can provide ideas for selecting processing parameters in industrial production.While guaranteeing the characteristic information is similar,this approach can select processing parameters which is the most appropriate for the production process and a lot of time can be saved.

Relational Turkish Text Classification Using Distant Supervised Entities and Relations

Text classification,by automatically categorizing texts,is one of the foundational elements of natural language processing applications.This study investigates how text classification performance can be improved through the integration of entity-relation information obtained from the Wikidata(Wikipedia database)database and BERTbased pre-trained Named Entity Recognition(NER)models.Focusing on a significant challenge in the field of natural language processing(NLP),the research evaluates the potential of using entity and relational information to extract deeper meaning from texts.The adopted methodology encompasses a comprehensive approach that includes text preprocessing,entity detection,and the integration of relational information.Experiments conducted on text datasets in both Turkish and English assess the performance of various classification algorithms,such as Support Vector Machine,Logistic Regression,Deep Neural Network,and Convolutional Neural Network.The results indicate that the integration of entity-relation information can significantly enhance algorithmperformance in text classification tasks and offer new perspectives for information extraction and semantic analysis in NLP applications.Contributions of this work include the utilization of distant supervised entity-relation information in Turkish text classification,the development of a Turkish relational text classification approach,and the creation of a relational database.By demonstrating potential performance improvements through the integration of distant supervised entity-relation information into Turkish text classification,this research aims to support the effectiveness of text-based artificial intelligence(AI)tools.Additionally,it makes significant contributions to the development ofmultilingual text classification systems by adding deeper meaning to text content,thereby providing a valuable addition to current NLP studies and setting an important reference point for future research.

Optimization of Agricultural Industrial Structure in Changping District of Beijing Based on Grey Relational Analysis

In the economic development of Beijing,although the share of the total amount of agricultural industry in the overall economy is relatively low,it has an important impact on the daily life of residents,social stability and the development of other industries.Changping District,as an important agricultural production base of Beijing,its agricultural development has an indispensable strategic significance for the stability and growth of the entire regional economy.Therefore,it is very important to study the structure of agricultural industry in Changping District.Based on the detailed analysis of the agricultural industrial structure of Changping District,this paper uses the grey relation theory to analyze the different industries in the agricultural industrial structure of Changping District,including planting,forestry,animal husbandry,fishery and agricultural,forestry,service industries,in order to reveal the impact of these industries on the agricultural industrial structure of Changping District.Through this study,it comes up with specific and feasible suggestions for the optimization of agricultural industrial structure in Changping District,and provides valuable reference for the agricultural development of other areas in Beijing.

Enhancing Relational Triple Extraction in Specific Domains:Semantic Enhancement and Synergy of Large Language Models and Small Pre-Trained Language Models

In the process of constructing domain-specific knowledge graphs,the task of relational triple extraction plays a critical role in transforming unstructured text into structured information.Existing relational triple extraction models facemultiple challenges when processing domain-specific data,including insufficient utilization of semantic interaction information between entities and relations,difficulties in handling challenging samples,and the scarcity of domain-specific datasets.To address these issues,our study introduces three innovative components:Relation semantic enhancement,data augmentation,and a voting strategy,all designed to significantly improve the model’s performance in tackling domain-specific relational triple extraction tasks.We first propose an innovative attention interaction module.This method significantly enhances the semantic interaction capabilities between entities and relations by integrating semantic information fromrelation labels.Second,we propose a voting strategy that effectively combines the strengths of large languagemodels(LLMs)and fine-tuned small pre-trained language models(SLMs)to reevaluate challenging samples,thereby improving the model’s adaptability in specific domains.Additionally,we explore the use of LLMs for data augmentation,aiming to generate domain-specific datasets to alleviate the scarcity of domain data.Experiments conducted on three domain-specific datasets demonstrate that our model outperforms existing comparative models in several aspects,with F1 scores exceeding the State of the Art models by 2%,1.6%,and 0.6%,respectively,validating the effectiveness and generalizability of our approach.

Optimization of short-circuit transition parameters of Q235B steel GMAW based on orthogonal gray relational analysis

In gas metal arc welding(GMAW)process,the short-circuit transition was the most typical transition observed in molten metal droplets.This paper used orthogonal tests to explore the coupling effect law of welding process parameters on the quality of weld forming under short-circuit transition,the design of 3 factors and 3 levels of a total of 9 groups of orthogonal tests,welding current,welding voltage,welding speed as input parameters:effective area ratio,humps,actual linear power density,aspect ratio,Vickers hardness as output paramet-ers(response targets).Using range analysis and trend charts,we can visually depict the relationship between input parameters and a single output parameter,ultimately determining the optimal process parameters that impact the single output index.Then combined with gray the-ory to transform the three response targets into a single gray relational grade(GRG)for analysis,the optimal combination of the weld mor-phology parameters as follows:welding current 100 A,welding voltage 25 V,welding speed 30 cm/min.Finally,validation experiments were conducted,and the results showed that the error between the gray relational grade and the predicted value was 2.74%.It was observed that the effective area ratio of the response target significantly improved,validating the reliability of the orthogonal gray relational method.

Advancements in Time Modeling: Relationalism, Divisional Structures, and Geometry

This article broadens terminology and approaches that continue to advance time modelling within a relationalist framework. Time is modeled as a single dimension, flowing continuously through independent privileged points. Introduced as absolute point-time, abstract continuous time is a backdrop for concrete relational-based time that is finite and discrete, bound to the limits of a real-world system. We discuss how discrete signals at a point are used to temporally anchor zero-temporal points [t = 0] in linear time. Object-oriented temporal line elements, flanked by temporal point elements, have a proportional geometric identity quantifiable by a standard unit system and can be mapped on a natural number line. Durations, line elements, are divisible into ordered unit ratio elements using ancient timekeeping formulas. The divisional structure provides temporal classes for rotational (Rt24t) and orbital (Rt18) sample periods, as well as a more general temporal class (Rt12) applicable to either sample or frame periods. We introduce notation for additive cyclic counts of sample periods, including divisional units, for calendar-like formatting. For system modeling, unit structures with dihedral symmetry, group order, and numerical order are shown to be applicable to Euclidean modelling. We introduce new functions for bijective and non-bijective mapping, modular arithmetic for cyclic-based time counts, and a novel formula relating to a subgroup of Pythagorean triples, preserving dihedral n-polygon symmetries. This article presents a new approach to model time in a relationalistic framework.

Materials Selection of Thermoplastic Matrices of Natural Fibre Composites for Cyclist Helmet Using an Integration of DMAIC Approach in Six Sigma Method Together with Grey Relational Analysis Approach

Natural fibre reinforced polymer composite(NFRPC)materials are gaining popularity in the modern world due to their eco-friendliness,lightweight nature,life-cycle superiority,biodegradability,low cost,and noble mechanical properties.Due to the wide variety of materials available that have comparable attributes and satisfy the requirements of the product design specification,material selection has become a crucial component of design for engineers.This paper discusses the study’s findings in choosing the suitable thermoplastic matrices of Natural Fibre Composites for Cyclist Helmet utilising the DMAIC,and GRA approaches.The results are based on integrating two decision methods implemented utilising two distinct decision-making approaches:qualitative and quantitative.This study suggested thermoplastic polyethylene as a particularly ideal matrix in composite cyclist helmets during the selection process for the best thermoplastic matrices material using the 6σtechnique,with the decision based on the highest performance,the lightest weight,and the most environmentally friendly criteria.The DMAIC and GRA approach significantly influenced the material selection process by offering different tools for each phase.In the future study,selection technique may have been more exhaustive if more information from other factors had been added.

Multi-Criteria Group Decision-Making Method Based on an Improved Single-Valued Neutrosophic Hamacher Weighted Average Operator and Grey Relational Analysis

This paper proposes a multi-criteria decision-making (MCGDM) method based on the improved single-valued neutrosophic Hamacher weighted averaging (ISNHWA) operator and grey relational analysis (GRA) to overcome the limitations of present methods based on aggregation operators. First, the limitations of several existing single-valued neutrosophic weighted averaging aggregation operators (i.e. , the single-valued neutrosophic weighted averaging, single-valued neutrosophic weighted algebraic averaging, single-valued neutrosophic weighted Einstein averaging, single-valued neutrosophic Frank weighted averaging, and single-valued neutrosophic Hamacher weighted averaging operators), which can produce some indeterminate terms in the aggregation process, are discussed. Second, an ISNHWA operator was developed to overcome the limitations of existing operators. Third, the properties of the proposed operator, including idempotency, boundedness, monotonicity, and commutativity, were analyzed. Application examples confirmed that the ISNHWA operator and the proposed MCGDM method are rational and effective. The proposed improved ISNHWA operator and MCGDM method can overcome the indeterminate results in some special cases in existing single-valued neutrosophic weighted averaging aggregation operators and MCGDM methods.

青年强则国强:青年人口学前瞻与优化青年人口发展

从当年梁启超发出历史呼号“少年强则国强”、李大钊提出“青春中华之创造”到如今党的二十大报告发出时代强音“青年强,则国家强”,显示了一脉相承的青少年与国家发展联系紧密的认识逻辑。本文回顾和界定了青年及青年人口学的内涵,认为青年可定义为“风险型人口”和“资源型人口”两大类,继而讨论了“青年强”的三重含义,即青年人口储备充足、青年人口素质卓越和青年人口红利丰厚,充分诠释了“青年强,则国家强”时代命题的深刻内涵。概言之,人尽其才则“青年强”,才尽其用则“国家强”。本文从国际比较的视角阐述了我国青年人口发展面临的问题和挑战,突出表现为:中国未来青年人口数量将长期处于缩减状态;青年人口的科学文化素质、身体健康素质和思想素质都有待“提质增效”;就业不充分,青年人口红利没有被充分释放。因此,要优化青年人口发展、进一步增强青年力量,采取相应的对策来强化青年人口储备、优化青年人口素质、极化青年人口红利、激发全人口活力。在人口负增长时代,建设适宜青年生存与发展的青年友好型社会极为必要,把解决青年问题作为解决低生育率等社会人口问题的重要突破口迫在眉睫。

DRG支付背景下某公立医院专科建设思考及实施效果分析

近年来,随着医改的持续深化,按疾病诊断相关分组(DRG)支付逐渐成为新医改的焦点。DRG支付制度不仅是医保结付的方式,同时也是公立医院规范医生诊疗行为、衡量医疗服务质量的管理工具,促使医院由粗放管理转向精细管理转型,对公立医院的运营管理理念提出一系列挑战。因此,分析DRG支付方式改革给公立医院带来的影响以及相关运营情况意义重大。笔者选取某公立医院推进DRG支付方式改革以来的22 791例病案资料进行分析,探讨在DRG支付背景下医院运营的应对策略及主要问题,为公立医院更好地落实DRG支付政策及高质量发展转型提供建议。

涉农高校助力乡村振兴的新型组织模式探索与实践——以吉林农业科技学院为例

乡村振兴战略是党的十九大提出的解决“三农”问题、加快农业农村现代化发展的重要举措。涉农高校在乡村振兴战略实施中具有独特优势,且肩负着重要使命。以吉林农业科技学院为例,提出涉农高校助力乡村振兴战略实施“五结合”新型组织模式,即“线上+线下”“集中+分散”“学校+企业”“项目+成果”“工作站+产业学院”,可为涉农高校服务乡村振兴战略提供借鉴,为乡村振兴发展提供新的思路和方法。

菲律宾小马科斯政府南海政策变化解析

自小马科斯政府上台以来,菲律宾的南海政策发生了一些非常明显的变化,包括不断在南海挑起事端,试图固化对仁爱礁的长期占有并重返黄岩岛,强化美菲军事同盟关系,积极开展同美西方在南海地区的安全合作,加大“舆论加法律”攻势,通过炒作南海问题来博取国际社会支持等。这些变化的出现,既是菲律宾国家安全重心调整和转向的结果,也是家族政治与权力斗争激发和助推的结果,更是美国在对华竞争背景下鼓动和支持菲律宾的结果。这在很大程度上恶化了地区安全环境,影响了中国的维权效能,也为美国推进其对华战略竞争创造了有利条件,并将对中菲两国关系的发展产生强烈的冲击。不过,由于受到多种因素的影响和制约,菲律宾的南海政策不会就此发生根本性的逆转,中菲南海争端也不可能由此变得一发不可收拾。为此,中国应当采取一些更为有效的政策和措施予以理性应对。

论国际关系研究的知识属性——兼论西方国际关系研究的内在缺陷

现代国际关系研究经历百年发展历程之后,正面临着新的机会和选择,需对其基本属性进行重新定位和认识。国内政治与国际关系在本体论层面上的差异决定了政治学与国际关系研究在方法论意义上的根本性差异,国家这个分析单元的个体性而非一般性特征是国际关系研究必须关注的重点。对“科学化”的过分追求可能导致国际关系研究陷入体系性和实践性之间的矛盾,对国际关系研究而言,任何追求简单性、普遍性和体系性的方法可能都未必真正有效,能够切合国际关系实际的,也许是一种更注重复杂性、个体性和特殊性的方法。国际关系研究中找回特殊性应加强对历史研究的关注和对社会研究的借鉴,并注重对文化和价值问题的分析。国际关系的知识应该是一种同时面向个体性、可变性和可能性并高度关注文化和价值因素的知识,既包括传统意义上的科学面向,也需要有新的追求,即降低国家行为的不确定性并探讨国家行为的可能性。这种追求,应该能够为国际关系研究开掘更广阔且更具实效性的空间。

6个苇状羊茅(型)品种在成都平原区的生产性能评价

为筛选适宜成都平原推广利用的优异牧草品种,对6个苇状羊茅(型)品种进行了生育期、主要农艺性状、鲜(干)草产量及牧草营养成分等指标的测定,并运用灰色关联度分析进行综合评价。结果表明,‘特沃’和‘科瑞’的生育期最长,均达275 d。各参试品种平均再生速度依次为‘马胡丽娜’>‘科瑞’>‘都脉’>‘特沃’>‘K31’>‘福泰’。品种‘马胡丽娜’年平均干草产量最高,可达12790.99 kg·hm-2,分别较国审品种‘特沃’和‘都脉’显著增加14.62%和4.28%(P<0.05),表现出明显的产量优势。‘科瑞’干草产量较‘特沃’显著增加6.59%(P<0.05),且植株自然高度可达100.15 cm,高于‘特沃’和‘都脉’(P<0.05)。‘都脉’的分蘖数最大,为47.33个·株^(-1),显著高于其他品种(P<0.05),其次是‘科瑞’和‘马胡丽娜’,分别达37.50和37.00个·株^(-1),较品种‘特沃’多6.25和5.75个·株^(-1)。‘K31’茎叶比为0.96,高于其他参试品种。对6个参试品种的营养成分测定表明,‘特沃’的粗蛋白含量最高,可达18.60%,‘科瑞’的粗脂肪含量最高,可达5.41%。通过灰色关联度法综合比较分析,‘科瑞’表现最优,‘特沃’和‘马胡丽娜’综合性状表现较优,适宜在成都平原地区推广种植利用。

“两对关系”论:费孝通对中国式现代化道路的学术探索

中国式现代化是中国几代人的梦想和夙愿。综观费孝通的学术历程,他终其一生都在探究如何让中国这样一个具有特色的大国走向现代化的问题。正是秉持这种学术理念,费孝通以实地研究为基本方法,从解决好城乡关系和民族关系切入,为推进中国式现代化作出了极富洞见的探索。这种探索对于当前立足中国国情,破除西方式现代化的迷思具有重要的贡献。

百年变局之变、历史启示及中国的战略选择

当今世界处于百年未有之大变局,“东升西降”的历史大势与国际体系加速转型相互叠加演进,而中国也正处于实现第二个百年奋斗目标、实现中华民族伟大复兴的关键时期。客观冷静地厘清世界百年变局的内涵要义,是准确把握当前国际形势风云变幻的逻辑起点。中国未来发展,需要顺应时代特征、国际格局、大国关系、全球治理、世界矛盾的新变化进行战略运筹谋划。对比中国和其他国家百年发展走过的道路与取得的经验,有助于更加坚定中国式现代化发展的基本遵循和道路方向,进一步增强在新的动荡变革期把握战略机遇、驾驭战略风险的能力。

涉外法治人才的分类与培养模式探讨

习近平总书记指出:“要加强涉外法治人才建设”。涉外法治人才包括涉外法律人才和国际法治人才。他们因工作侧重点不同,职业素养和外语能力要求也不一样。涉外法律人才与国内其他类型的法律人才没有本质区别,都是适用中国法律解决具体问题,只不过涉外法律人才因其工作的涉外特点,还要了解相关国家的法律和掌握这个国家的语言。国际法治人才是适用国际规则处理国与国之间的关系和解决全人类共同关心的问题。因此,除了熟悉相关国际条约,国际法治人才还必须精通国际通用的工作语言。涉外法律人才用他们的法律专业知识化解各类涉外纠纷,推动我国的经济建设和对外开放;国际法治人才在处理好国与国关系的同时,还要履行维护世界和平、促进全人类共同繁荣的使命。

免疫治疗相关性甲状腺功能异常与不可切除/晚期肝细胞癌患者预后改善相关

目的:探讨免疫治疗相关性甲状腺功能异常与不可切除/晚期肝细胞癌(HCC)患者预后改善的相关性。方法:回顾性分析45例接受免疫检查点抑制剂(ICIs)治疗的不可切除/晚期HCC患者。根据ICIs治疗过程中是否出现免疫相关性甲状腺功能异常分为甲状腺功能正常组(28例)和异常组(17例),比较2组患者的预后和免疫应答情况,主要终点指标为中位总生存期(OS)、无进展生存期(PFS),次要终点指标为疾病控制率(DCR)。结果:所有患者的中位OS、PFS分别为10.8个月(95%CI:3.0~18.6)和5.0个月(95%CI:3.0~12.2)。正常组中位OS为5.8个月(95%CI:3.7~7.9),异常组中位OS尚未达到(P=0.026)。异常组中位PFS长于正常组(8.2个月vs.3.1个月,P=0.011),DCR高于正常组(52.9%vs.21.5%,P=0.030)。多因素Cox回归分析显示,甲状腺功能异常是达到6个月OS(HR=0.213,95%CI:0.048~0.944,P=0.042)和PFS(HR=0.383,95%CI:0.151~0.967,P=0.042)的独立影响因素;甲状腺功能异常(HR=0.403,95%CI:0.185~0.877,P=0.022)、基线无大血管侵犯(MVI)(HR=2.848,95%CI:1.406~5.768,P=0.004)、Child-Pugh A级(HR=2.404,95%:1.099~5.255,P=0.028)与12个月PFS相关。结论:免疫治疗相关性甲状腺功能异常的不可切除/晚期HCC患者预期生存和免疫应答效果更佳。治疗期间出现甲状腺功能异常、基线无MVI、Child-Pugh A级与患者预后改善相关。

糖调节受损患者血清25(OH)D和免疫相关因子对亚临床动脉粥样硬化影响的研究

目的:研究糖调节受损患者血清25(OH)D和免疫相关因子对亚临床动脉粥样硬化(AS)的影响。方法:选取2019年12月至2021年4月枣庄市立医院收治的142例糖调节受损患者,根据经颈动脉超声检查和臂踝脉搏波传导速度分组,仅糖调节受损患者为对照组(n=86),并发亚临床AS为观察组(n=56)。比较两组患者血清25(OH)D和免疫因子,应用颈动脉超声检测测定颈动脉内中膜厚度,Pearson法测定血清颈动脉内中膜厚度与血清25(OH)D和免疫因子的相关性。采集基线资料和血液学指标,单因素和多因素Logistic回归分析确定亚临床AS的影响因素,应用ROC曲线评估血清25(OH)D和免疫因子对亚临床AS的诊断效能。结果:观察组患者血清25(OH)D[(24.01±4.87)mmol/L vs 3(0.74±5.01)mmol/L,t=7.909,P=0.000)明显低于对照组,观察组患者TNF-α[(48.32±8.02)ng/L vs(33.21±9.00)ng/L,t=10.199,P=0.000)和IL-6[(41.22±9.43)ng/L vs(30.21±7.01)ng/L,t=7.492,P=0.000)明显高于对照组。颈动脉内中膜厚度与血清25(OH)D呈负相关(r=-0.428,P<0.001),颈动脉内中膜厚度与血清TNF-α和IL-6呈正相关(r=0.574,0.577,P<0.001)。Logistic回归分析结果表明,血清25(OH)D(OR=0.520,95%CI:0.401~0.675)、血清TNF-α(OR=1.667,95%CI:1.131~2.457)和血清IL-6(OR=1.478,95%CI:1.213~1.802)等是亚临床AS发生的影响因素。ROC曲线结果显示,血清25(OH)D最佳截断值为28.32 mmol/L,其对应的敏感度为69.64%,特异度为70.93%,AUC为0.803(95%CI:0.749~0.855);血清TNF-α临界值为40.56 ng/L,其对应的敏感度为71.43%,特异度为72.09%,AUC为0.761(95%CI:0.717~0.823);血清IL-6截断值为36.13 ng/L,其对应的敏感度为60.71%,特异度为60.47%,AUC为0.627(95%CI:0.566~0.702);回归分析对应的敏感度为85.71%,特异度为81.40%,AUC为0.889(95%CI:0.830~0.915)。结论:血清25(OH)D与免疫相关因子单独和联合回归检测可有效预测亚临床AS的发生,上述指标与颈动脉内中膜厚度相关,且血清25(OH)D和免疫相关因子是亚临床AS发生的预测指标,临床宜根据指标进行针对性干预,值得进一步研究。