How Software Engineering Transforms Organizations: An Open and Qualitative Study on the Organizational Objectives and Motivations in Agile Transformations

Agile Transformations are challenging processes for organizations that look to extend the benefits of Agile philosophy and methods beyond software engineering.Despite the impact of these transformations on orga-nizations,they have not been extensively studied in academia.We conducted a study grounded in workshops and interviews with 99 participants from 30 organizations,including organizations undergoing transformations(“final organizations”)and companies supporting these processes(“consultants”).The study aims to understand the motivations,objectives,and factors driving and challenging these transformations.Over 700 responses were collected to the question and categorized into 32 objectives.The findings show that organizations primarily aim to achieve customer centricity and adaptability,both with 8%of the mentions.Other primary important objectives,with above 4%of mentions,include alignment of goals,lean delivery,sustainable processes,and a flatter,more team-based organizational structure.We also detect discrepancies in perspectives between the objectives identified by the two kinds of organizations and the existing agile literature and models.This misalignment highlights the need for practitioners to understand with the practical realities the organizations face.

An Exploration of Organizational Development in the Process of Innovation and Transformation of Pharmaceutical Enterprises-Taking X Pharmaceutical Enterprise as an Example

Objective To study how to promote the smooth innovation and transformation of enterprises and enhance the market competitiveness of enterprises from the perspective of human resources organization development.In the wave of pharmaceutical industry reform,some entrepreneurs realize the importance of innovation and technology in the future.However,domestic pharmaceutical enterprises are still in the production-oriented stage.In the process of transformative innovation,pharmaceutical enterprises should not only rely on the support of scientific and technological and economic forces,but also need a suitable organizational change and many excellent talents as the source of development.Methods Through retrieving relevant literature and combined with the organizational development practice of X pharmaceutical enterprise,the organizational development model was explored in this paper.Results and Conclusion By forming a system of strategy,organization,talent,culture and mechanism,and building an organizational development model,we can improve the organizational atmosphere and organizational efficiency in the process of enterprise innovation and transformation,so as to enhance the competitiveness of enterprises in the market.

Molecular investigation into the transformation of recalcitrant dissolved organic sulfur in refinery sour water during stripping process

Refinery sour water primarily originates from the tops of towers in various units and coker condensate,and cannot be discharged directly to a wastewater treatment plant due to high levels of chemical oxygen demand(COD)and organic sulfur contents.Even after the recovery of H_(2)S from the sour water by the stripping process,the effluent still contains a high concentration of dissolved organic sulfur(DOS),which can have a huge bad influence.While chemical composition of dissolved organic matter(DOM)in refinery wastewater has been extensively studied,the investigation of recalcitrant DOS from sour waters remains unclear.In the present study,chemical composition of sour water DOMs(especially DOS)was investigated using fluorescence spectroscopy(excitation-emission matrix,EEM)and mass spectrometry,including gas chromatography-mass spectrometry(GC-MS)and high-resolution Orbitrap MS.The GC-MS and EEM results showed that volatile and low-aromaticity compounds were effectively removed during the stripping process,while compounds with high hydrophilicity and humification degree were found to be more recalcitrant.The Orbitrap MS results showed that weak-polar oxygenated sulfur compounds were easier to be removed than oxygenated compounds.However,the effluent still contained significant amounts of sulfur-containing compounds with multiple sulfur atoms,particularly in the form of highly unsaturated and aromatic compounds.The Orbitrap MS/MS results of CHOS-containing compounds from the effluent indicate that the sulfur atoms may exist as sulfonates,disulfide bonds,thioethers.Understanding the composition and structure of sour water DOS is crucial for the development of effective treatment processes that can target polysulfide compounds and minimize their impact on the environment.

The Polish SMEs as Intelligent Organizations in an Era of Digital Transformation

The impact that the digital transformation(DT)has on businesses,suppliers,and other third parties has increased significantly now.Digital transformation means improving traditional manufacturing processes with the help of digital technologies.The goal of digital transformation is to increase production efficiency and reduce costs,improve the quality of goods and services produced,and quickly adapt to changes in the global market.The state of industrial production is constantly changing due to the instability of global,economic and political decisions,so the adoption and expansion of digital solutions based on Industry 4.0,the Internet of things,machine learning,and other technologies of the future is accelerating.With the help of these technologies,companies are trying to change approaches and find new ways to solve problems.In this article the author analyzed the phenomenon of a complex system of knowledge management with tools as SMAC,AI,IoT and Edge computing in intelligent organizations as a part of intelligent economy.The arguments are illustrated with the results of own research conducted by the author in 2021-2022 in selected SMEs from the Polish Wielkopolska Province and their reference to the general development trends in this area.

Organic matter transformation ratio, hydrocarbon expulsion efficiency and shale oil enrichment type in Chang 7_(3) shale of Upper Triassic Yanchang Formation in Ordos Basin, NW China

The major enrichment type of shale oil in the Chang 7_(3) shale of Upper Triassic Yanchang Formation in the Ordos Basin is unknown.This paper analyzes the organic matter transformation ratio,hydrocarbon expulsion efficiency and roof/floor sealing conditions of the Chang 7_(3) shale,and evaluates the major enrichment type of shale oil in this interval.The average organic matter transformation ratio of the Chang 7_(3) shale is about 45%;in other words,more than 50%of the organic matters have not transformed to hydrocarbons,and the lower the maturity,the greater the proportion of untransformed organic matters.The cumulative hydrocarbon expulsion efficiency of the transformed hydrocarbon is 27.5% on average,and the total proportion of untransformed organic matters plus retained hydrocarbons is greater than 70%.The relative hydrocarbon expulsion efficiency of the Chang 7_(3) shale is 60%on average,that is,about 40% of hydrocarbons retain in the shale.The Chang 7_(3) shale corresponds to Chang 7_(1+2) and Chang 8 sandstones as the roof and floor,respectively,and is further overlaid by Chang 6 shale,where extensive low porosity and low permeability–tight oil reservoirs have formed in the parts with relatively good porosity and permeability.Moreover,the Chang 7_(3) shale is tested to be in a negative pressure system(the pressure coefficient of 0.80–0.85).Therefore,the roof/floor sealing conditions of the Chang 7_(3) shale are poor.The retained hydrocarbons appear mostly in absorbed status,with low mobility.It is concluded that the medium–high mature shale oil is not the major enrichment type of shale oil in the Chang 7_(3) shale,but there may be enrichment opportunity for shale oil with good mobility in the areas where the sealing conditions are good without faults and fractures and oil reservoirs are formed off Chang 7_(1+2),Chang 6 and Chang 8.Furthermore,low–medium mature shale oil is believed to have great potential and is the major enrichment type of shale oil in the Chang 7_(3) shale.It is recommended to prepare relevant in-situ conversion technologies by pilot test and figure out the resource availability and distribution.

基于CNN和Transformer并行编码的腹部多器官图像分割

针对现有方法在腹部中小器官图像分割性能方面存在的不足,提出一种基于局部和全局并行编码的网络模型用于腹部多器官图像分割.首先,设计一种提取多尺度特征信息的局部编码分支;其次,全局特征编码分支采用分块Transformer,通过块内Transformer和块间Transformer的组合,既捕获了全局的长距离依赖信息又降低了计算量;再次,设计特征融合模块,以融合来自两条编码分支的上下文信息;最后,设计解码模块,实现全局信息与局部上下文信息的交互,更好地补偿解码阶段的信息损失.在Synapse多器官CT数据集上进行实验,与目前9种先进方法相比,在平均Dice相似系数(DSC)和Hausdorff距离(HD)指标上都达到了最佳性能,分别为83.10%和17.80 mm.

Could One Transformational Leader Convert the Organization From Knowledge Based Into Learning Organization, Then Into Innovation？

This paper examines the role of transformational leadership in transforming an organization into a knowledge based, then into learning organization so that it becomes an innovative company. Important features of the leader such and ability to assist in developing and accommodating the implementation of knowledge management programs, learning organization concepts and innovation protocols are discussed in this paper. This paper demonstrates that shifting the organization to become a knowledge based and then to be learning organization and finally to become innovative company could involve some unique attributes of a transformation leadership. In that regards, the paper also demonstrates that organizations need first to create, capture, transfer, and mobilize knowledge before it can be used for learning and then for innovation. The paper will present a method of a studying how successful innovation leaders of companies could found themselves acting in three roles namely： knowledge leader, learning leader and then innovation leader.

基于改进YOLOv5s的CNN-Swin Transformer森林野生动物图像目标检测算法

【目的】为提高野生动物在复杂森林环境中的检测精度,促进森林野生动物保护技术发展,提出一种基于YOLOv5s网络模型、针对陷阱相机所摄取森林野生动物图像的改进检测算法。【方法】以包含湖南壶瓶山国家级自然保护区几种典型森林野生动物在内的数据集为研究对象,首先,对真实标注框图像进行裁剪、归一化和缩放处理,随机将2~4张裁剪图像拼贴组成新的数据集元素,以丰富和增强数据集图像信息;其次,使用一种基于通道注意力思想的加权通道拼接方法,在通道拼接时引入权重改变通道数量,通过反向传播训练方法不断更新权重以增加重要特征信息的通道层数;接着,引入Swin Transformer模块与CNN网络相结合,为卷积神经网络特征提取加入自注意力机制,融合2种网络特征提取层的优势,提高特征提取的感受野;最后,选择更优的α-DIoU损失函数替代GIoU损失函数,针对边界框重叠面积和中心点距离造成的损失,引入新的几何因素惩罚项。【结果】在相同试验条件和数据集下,相比原YOLOv5s网络模型,改进算法极大提高检测的平均准确率和平均回归率,均值平均精度由74.1%提升至88.4%,获得14.3%的精度提升,同时也超过YOLOv3、YOLOXs、RetinaNet、Faster R-CNN等其他流行目标检测算法。【结论】针对陷阱相机所摄取森林野生动物图像背景与目标对比度低、遮挡重叠严重,致使检测误检率、漏检率高等问题,在检测算法中提出一系列改进措施,为我国森林野生动物的保护和数据获取提供一种新的可行性方案和思路。

基于Transformer改进YOLOv5的交通标志检测算法

交通标志检测作为自动驾驶的组成部分直接影响着行车安全。针对现有算法对图像中尺寸小、被遮挡的标志存在漏检、误检的问题,文中提出了基于改进YOLOv5的交通标志检测算法。首先对原模型注意力缺失的问题经过对比后构建了BiFormer-y,使模型可以更好获取长期依赖;接着针对层数较深造成的具有丢失特征的缺陷,利用残差结构重新设计检测层,从而更好地保留特征;最后对耦合头的空间错位问题引入解耦头并进行优化。CCTSDB2021的实验表明,精确率、召回率、mAP分别为97.0、95.9、97.9与先进工作相比具有明显优势。

融合卷积和Transformer的腹部多器官分割网络

腹部多器官分割在计算机辅助诊断中起着至关重要的作用,具有重要的研究价值。但由于腹部多器官边界模糊、背景复杂以及形状大小多变,使这项任务极具挑战性。为此,提出了一种融合卷积和Transformer的腹部多器官分割网络TCMSUnet。首先,在特征提取阶段设计了多尺度引导融合模块(GFM),利用高层特征提取的显著语义信息来引导低层特征以增强相邻特征的语义一致性,从而促进不同尺度特征的融合;随后设计了全局局部增强模块(GLE),通过空洞卷积和Transformer块结合来增强模型对全局局部上下文信息的提取,使模型在建立长距离依赖关系的同时加强特征的局部关联性;最后,在解码器部分引入多阶段损失聚合结构以加快模型的收敛并优化模型的性能。在Synapse数据集上评估了模型的性能,其平均Dice相似系数(DSC)为81.20%。实验结果表明,所提方法整体性能优于多种比较网络,并对形状大小多变的器官有更好的分割效果。

Application of sparse S transform network with knowledge distillation in seismic attenuation delineation

Time-frequency analysis is a successfully used tool for analyzing the local features of seismic data.However,it suffers from several inevitable limitations,such as the restricted time-frequency resolution,the difficulty in selecting parameters,and the low computational efficiency.Inspired by deep learning,we suggest a deep learning-based workflow for seismic time-frequency analysis.The sparse S transform network(SSTNet)is first built to map the relationship between synthetic traces and sparse S transform spectra,which can be easily pre-trained by using synthetic traces and training labels.Next,we introduce knowledge distillation(KD)based transfer learning to re-train SSTNet by using a field data set without training labels,which is named the sparse S transform network with knowledge distillation(KD-SSTNet).In this way,we can effectively calculate the sparse time-frequency spectra of field data and avoid the use of field training labels.To test the availability of the suggested KD-SSTNet,we apply it to field data to estimate seismic attenuation for reservoir characterization and make detailed comparisons with the traditional time-frequency analysis methods.

Gender and rural transformation:A systematic literature review

Rural transformation can improve poverty reduction,living standards,and health outcomes in developing countries.However,impacts associated with rural transformation vary by region,household,and individual trait(including gender).While research on rural transformation has been increasing over the last decade,there has been no comprehensive review conducted on the relationships between gender and rural transformation.Here,we conduct a systematic literature review to investigate the impacts of rural transformation on gender and the influence of gender inclusiveness on rural transformation.We reviewed 82 studies from 1960-2021 that explore the relationships between rural transformation and gender.We then developed a framework that captures incidences and flow directions between indicators.Results show that most studies examined the impacts of rural transformation on women and between gender indicators.Few investigated the role of women and the influence of gender inclusiveness on rural transformation.Overall,studies showed that rural transformation typically leads to positive outcomes for women regarding employment,income,and empowerment.However,negative impacts on women’s control over income,stability of new income sources,and access to healthy food are also common.Tailoring future development policies and programs to explicitly account for gender inclusiveness can lead to more successful rural transformation.

多级特征交互Transformer的多器官图像分割

多器官医学图像分割有助于医生做出临床诊断.针对CNN提取全局特征能力弱,Transformer提取局部特征能力弱,以及Transformer具有二次方计算复杂度的问题,提出了用于多器官医学图像分割的多级特征交互Transformer模型.所提模型采用CNN提取局部特征,局部特征经Swin Transformer输出全局特征;通过下采样分别产生多级局部和全局特征,每级局部和全局特征经过交互并增强;每级增强后的特征经多级特征融合模块进行交叉融合;再次融合后的特征经过上采样和分割头输出分割掩码.所提模型在Synapse和ACDC数据集上进行实验,平均DSC和平均HD95系数值为80.16%和19.20 mm,均优于LGNet和RFE-UNet等代表性模型.该模型对多器官医学图像分割是有效的.

Longitudinal assessment of peripheral organ metabolism and the gut microbiota in an APP/PS1 transgenic mouse model of Alzheimer’s disease

Alzheimer’s disease not only affects the brain,but also induces metabolic dysfunction in peripheral organs and alters the gut microbiota.The aim of this study was to investigate systemic changes that occur in Alzheimer’s disease,in particular the association between changes in peripheral organ metabolism,changes in gut microbial composition,and Alzheimer’s disease development.To do this,we analyzed peripheral organ metabolism and the gut microbiota in amyloid precursor protein-presenilin 1(APP/PS1)transgenic and control mice at 3,6,9,and 12 months of age.Twelve-month-old APP/PS1 mice exhibited cognitive impairment,Alzheimer’s disease-related brain changes,distinctive metabolic disturbances in peripheral organs and fecal samples(as detected by untargeted metabolomics sequencing),and substantial changes in gut microbial composition compared with younger APP/PS1 mice.Notably,a strong correlation emerged between the gut microbiota and kidney metabolism in APP/PS1 mice.These findings suggest that alterations in peripheral organ metabolism and the gut microbiota are closely related to Alzheimer’s disease development,indicating potential new directions for therapeutic strategies.

基于Transformer与信息融合的绝缘子缺陷检测方法

针对现有绝缘子航拍图像背景复杂,闪络、破损缺陷检测困难的问题,本文提出一种全局与局部信息融合(GLIF)-YOLOv8s绝缘子缺陷检测算法。该算法采用EfficientFormerV2作为主干网络,以提高模型对全局信息的提取能力;基于全局与局部信息设计特征增强模块,通过信息融合减少深层网络信息的丢失。在绝缘子缺陷数据集上进行消融实验与对比实验,结果表明:本文算法在绝缘子缺陷数据集上的平均精度均值为91.6%,其对闪络和破损缺陷的检测平均精度分别达到82.3%和92.9%;与其他主流算法相比,本文算法的检测框置信度更高。

Plasma Levels of Transforming Growth Factor-Beta 1 in Women with Pelvic Organ Prolapse

Objective: In women with pelvic organ prolapse (POP), decreased expression of transforming growth factor-beta 1 (TGF-β1) has been shown in POP tissues. However, no studies have evaluated plasma TGF-β1 levels in patients with POP, so it is unknown whether they are also changed or not. Therefore, we compared plasma TGF-β1 levels in women with and without POP. Methods: Participants were 49 women with POP and 23 healthy control women. All participants were postmenopausal. We measured plasma TGF-β1 and compared data between patients with POP and controls, and between patients with uterine prolapse (UP, n = 19) and those with a cystocele (CC, n = 30). In addition, in patients, we assessed the POP quantification system (POP-Q) stage. Results: Plasma TGF-β1 levels were significantly lower in patients than in healthy controls. POP-Q stage was not significantly different between the UP and CC subgroups, but POP-Q stage IV was diagnosed in 63% of patients with UP and 7% of those with CC. Plasma TGF-β1 levels were significantly lower in the CC subgroup than in the UP subgroup. Conclusion: Plasma TGF-β1 is decreased in POP. It remains unclear whether the lower levels indicate a reduction in systemic TGF-β1 activity, but they can be assumed to reflect reduced TGF-β1 expression in POP tissues.

Changes in Transformation of Soil Organic C and Functional Diversity of Soil Microbial Community Under Different Land Uses

Changes in soil biological and biochemical properties under different land uses in the subtropical region of China were investigated in order to develop rational cultivation and fertilization management. A small watershed of subtropical region of China was selected for this study. Land uses covered paddy fields, vegetable farming, fruit trees, upland crops, bamboo stands, and forestry. Soil biological and biochemical properties included soil organic C and nutrient contents, mineralization of soil organic C, and soil microbial biomass and community functional diversity. Soil organic C and total N contents, microbial biomass C and N, and respiration intensity under different land uses were changed in the following order： paddy fields （and vegetable farming） 〉 bamboo stands 〉 fruit trccs （and upland）. The top surface （0-15 cm） paddy fields （and vegetable farming） were 76.4 and 80.8% higher in soil organic C and total N contents than fruit trees （and upland） soils, respectively. Subsurface paddy soils （15-30 cm） were 59.8 and 67.3% higher in organic C and total N than upland soils, respectively. Soil microbial C, N and respiration intensity in paddy soils （0-15 cm） were 6.36, 3.63 and 3.20 times those in fruit tree （and upland） soils respectively. Soil microbial metabolic quotient was in the order： fruit trees （and upland） 〉 forestry 〉 paddy fields. Metabolic quotient in paddy soils was only 47.7% of that in fruit tree （and upland） soils. Rates of soil organic C mineralization during incubation changed in the order： paddy fields 〉 bamboo stands 〉 fruit trees （and upland） and soil bacteria population： paddy fields 〉 fruit trees （and upland） 〉 forestry. No significant difference was found for fungi and actinomycetes populations. BIOLOG analysis indicated a changing order of paddy fields 〉 fruit trees （and upland） 〉 forestry in values of the average well cell development （AWCD） and functional diversity indexes of microbial community. Results also showed that the conversion from paddy fields to vegetable farming for 5 years resulted in a dramatic increase in soil available phosphorus content while insignificant changes in soil organic C and total N content due to a large inputs of phosphate fertilizers. This conversion caused 53, 41.5, and 41.3% decreases in soil microbial biomass C, N, and respiration intensity, respectively, while 23.6% increase in metabolic quotient and a decrease in soil organic C mineralization rate. Moreover, soil bacteria and actinomycetes populations were increased slightly, while fungi population increased dramatically. Functional diversity indexes of soil microbial community decreased significantly. It was concluded that land uses in the subtropical region of China strongly affected soil biological and biochemical properties. Soil organic C and nutrient contents, mineralization of organic C and functional diversity of microbial community in paddy fields were higher than those in upland and forestry. Overuse of chemical fertilizers in paddy fields with high fertility might degrade soil biological properties and biochemical function, resulting in deterioration of soil biological quality.

Study on Migration and Transformation Rule of Organic Pollutants (COD) in Aerated Zone

Collecting waste water with a certain c onc entration of organic pollutants COD (chemical oxygen demand), static adsorption, static biodegradation and dynamic soil column experiments were made in laborato ry, we researched migration and transformation of COD in aerated zone, and put f orward a mathematical model showing the process. The results show that adsorptio n of organism in aerated zone is linear, which is represented by Henry's law s =K dc+s d, adsorption coefficient K d=0.069 3; biodegradati on diagram accord basically with first order kinetics equation c=c 0e -K 1t , biodegradation coefficient K 1 = 0.049 9 d -1 ; dispersio n coefficient D= 0.002 42 m 2/d in experiments. The migration and transform ation of organic pollutants (COD) in aerated zone jointly result from many f actors such as dispersion, adsorption and biodegradation etc..

Transformation of organic N newly added to red soil treated with different cultural practices

ＴｒａｎｓｆｏｒｍａｔｉｏｎｏｆｏｒｇａｎｉｃＮｎｅｗｌｙａｄｄｅｄｔｏｒｅｄｓｏｉｌｔｒｅａｔｅｄｗｉｔｈｄｉｆｅｒｅｎｔｃｕｌｔｕｒａｌｐｒａｃｔｉｃｅｓＺｈａｎｇＱｉｎＺｈｅｎｇ，ＹｅＱｉｎｇＦｕ，ＸｉＨａｉＦｕａｎｄＷｕＧａｎｇ（Ｉｎ...

基于S-YOLO V5和Vision Transformer的视频内容描述算法

视频内容描述的自动生成是结合计算机视觉和自然语言处理等相关技术提出的一种新型交叉学习任务。针对当前视频内容生成描述模型可读性不佳的问题,本研究提出一种基于S-YOLO V5和Vison Transformer(ViT)的视频内容描述算法。首先,基于神经网络模型KATNA提取关键帧,以最少帧数进行模型训练;其次,利用S-YOLO V5模型提取视频帧中的语义信息,并结合预训练ResNet101模型和预训练C3D模型提取视频静态视觉特征和动态视觉特征,并对两种模态特征进行融合;然后,基于ViT结构的强大长距离编码能力,构建模型编码器对融合特征进行长距离依赖编码;最后,将编码器的输出作为LSTM解码器的输入,依次输出预测词,生成最终的自然语言描述。通过在MSR-VTT数据集上进行测试,本研究模型的BLEU-4、METEOR、ROUGEL和CIDEr分别为42.9、28.8、62.4和51.4;在MSVD数据集上进行测试,本研究模型的BLEU-4、METEOR、ROUGEL和CIDEr分别为56.8、37.6、74.5以及98.5。与当前主流模型相比,本研究模型在多项评价指标上表现优异。