Cross-contamination of CRISPR guides and other unrelated nucleotide sequences among commercial oligonucleotides.

Custom oligonucleotides (oligos) are widely used reagents in biomedical research. Some common applications of oligos include polymerase chain reaction (PCR), sequencing, hybridization, microarray, and library construction. The reliability of oligos in such applications depends on their purity and specificity. Here, we report that commercially available oligos are frequently contaminated with nonspecific sequences (i.e. other unrelated oligonucleotides). Most of the oligos that we designed to amplify clustered regularly interspersed palindromic repeats (CRISPR) guide sequences contained nonspecific CRISPR guides. These contaminants were detected in research-grade oligos procured from eight commercial oligo-suppliers located in three different geographic regions of the world. Deep sequencing of some of the oligos revealed a variety of contaminants. Given the wide range of applications of oligos, the impact of oligo cross-contamination varies greatly depending on the field and the experimental method. Incorporating appropriate control experiments in research design can help ensure that the quality of oligo reagents meets the intended purpose. This can also minimize risk depending on the purposes for which the oligos are used.

Common institutional investors and the quality of management earnings forecasts-Empirical and machine learning evidences.

Based on the data of the Chinese A-share listed firms in China Shanghai and Shenzhen Stock Exchange from 2014 to 2021, this article explores the relationship between common institutional investors and the quality of management earnings forecasts. The study used the multiple linear regression model and empirically found that common institutional investors positively impact the precision of earnings forecasts. This article also uses graph neural networks to predict the precision of earnings forecasts. Our findings have shown that common institutional investors form external supervision over restricting management to release a wide width of earnings forecasts, which helps to improve the risk warning function of earnings forecasts and promote the sustainable development of information disclosure from management in the Chinese capital market. One of the marginal contributions of this paper is that it enriches the literature related to the economic consequences of common institutional shareholding. Then, the neural network method used to predict the quality of management forecasts enhances the research method of institutional investors and the behavior of management earnings forecasts. Thirdly, this paper calls for strengthening information sharing and circulation among institutional investors to reduce information asymmetry between investors and management.

Carbon emission fluctuations of Chinese inter-regional interaction: a network multi-hub diffusion perspective.

The "double-carbon" policy is a new opportunity for the transformation of China's production sector. With steady economic growth, each province has proposed specific policies aimed at cleaner production. However, the interactions between regions and the complex linkages between industries have hindered the implementation of the "double-carbon" policy. In order to address this issue, we introduced a complex network framework with multiple industries at a national level. The framework aimed to clarify whether there is fluctuation diffusion in China's multi-province multi-industry carbon emission system, to identify key industries and regions, and to answer the question of "who" is the most effective in governance. The results showed that the fluctuations of industrial carbon emissions had a cross-regional diffusion effect in China indeed. The diffusion capacity of industry fluctuation depends on whether the industry is located at a "hub" position in the network. Hub industries with strong capacity can spread the carbon emission fluctuation of themselves and upstream or downstream industries to the whole country through regional interactions. This characteristic of the hub industry should be taken into account in governance to maximize the effectiveness of emission reduction. Shandong and Inner Mongolia, as important provinces for the production of intermediate products and energy chemicals in China, had a greater role to play in global carbon supply push from their hub industries than in the demand pull. The pulling capacity of Beijing-Tianjin-Hebei region to the national carbon demand side was greater than that of Yangtze River Delta and Pearl River Delta. These findings might have implications for environmental and economic policymaking, particularly with regard to cross-provincial coordinated systemic solutions and policy anchors for synergy with industries.

Skin Microbiota and the Cosmetic Industry.

Skin harbors an important microbial ecosystem - the skin microbiota that is in homeostasis with its host and is beneficial for human health. Cosmetic products have the potential to interfere with this microbial community; therefore their impact should be assessed. The aim of this review is to highlight the importance of skin microbiota in the cosmetic industry. Several studies determined that cosmetic ingredients have the potential to disrupt the skin microbiota equilibrium leading to the development of skin diseases and dysregulation of immune response. These studies led their investigation by using different methodologies and models, concluding that methods must be chosen according to the aim of the study, the skin site to be evaluated, and the target population of the cosmetics. Overall, it is crucial to test the impact of cosmetics in the skin microbiota and to stablish standard procedures, as well as specific criteria that allow to classify a cosmetic product as skin microbiota friendly.

Selection and Optimization of Regional Economic Industrial Structure Based on Fuzzy k-Means Clustering Algorithm.

Learning about the regional business model is essential for the sustainable development of the regional economy. From the perspective of urban renewable energy, city A is the product of energy development. This paper analyzes the current situation and existing problems of the industrial model of city A through fuzzy k-means clustering algorithm. The results show that although the optimization of industrial structure in city A has achieved some results, the more intuitive problems mainly include low labor productivity of the primary industry, strong resource dependence, insufficient extension of industrial chain, and slow development of technology intensive industries. This paper uses fuzzy k-means clustering algorithm to select the leading industries from the perspective of the current situation of leading industries, urban development pattern, and regional policies in city A. The results show that, as a renewable resource-based city, the leading industries suitable for the current development of city A include manufacturing, power, alkali gas and water production and supply, transportation, warehousing and postal industry, leasing, and business services. The results of fuzzy k-means clustering algorithm are quite excellent, and the accuracy rate is 93.3%. This paper uses the grey dynamic linear programming model to predict the future development of the Urban A business model and combines the selection of key functions to obtain the best business model: deep and efficient technical equipment as a good goal, achieved through regional logistics, transportation, new services, etc., to enhance the output value of the tertiary industry in city A and optimize the internal structure of the secondary industry in city A.

Energy efficiency of the industrial sectors in Beijing-Tianjin-Hebei urban agglomeration: does technological gap matter?

As the political and technological innovation center of China, Beijing-Tianjin-Hebei urban agglomeration (BTHUA) is an important engine of national economic development. However, the BTHUA is faced with uneven industrial development and environmental pollution problems. Energy efficiency of the industrial sector, critical to energy conservation and environmental protection, is the key to achieving green economic transformation. For this reason, this study adopts the parametric meta-frontier approach to measure the industrial total-factor energy efficiency (TFEE) of the BTHUA, centering on the evaluation of regional technology gap ratio (TGR). Empirical results indicate that there are significant regional disparities of industrial TFEE in the BTHUA. In particular, industrial TFEE tends to be underestimated without considering technological heterogeneity in production technology. The TGRs of manufacturing cities, tourist cities, and the modernized metropolis (Beijing) are the highest among the region. On this basis, the influencing factors of industrial TFEE of the BTHUA are further accessed based on the fixed effects model and the Tobit model. This article verifies that the evaluation of TFEE in the BTHUA must take regional technological gap into account, and provides additional empirical evidence on how to promote coordinated regional industrial development and energy efficiency improvement.

On the estimation of the fill rate for the continuous (s, S) inventory system for the lost sales context.

In the continuous review reorder point, base-stock (s, S) policy, the replenishment order is launched when the inventory position reaches the reorder point, s. It is commonly assumed that the inventory position is exactly equal to the reorder point at the moment the order is launched, when actually it could be lower at that moment. This implies neglecting the possible undershoots at the reorder point, which has a direct impact on the calculation of the expected shortages per replenishment cycle. This article presents a method for an exact calculation of the fill rate (fraction of demand that is immediately satisfied from shelf) which takes explicit account of the existence of undershoots and is applicable to any discrete demand distribution function in a context of lost sales. This method is based on the determination of the stock probability vector at the moment the replenishment order is launched. Furthermore, neglecting the undershoots is shown to lead to an overestimation of the fill rate, particularly when we move farther away from the unitary demand assumption. From a practical point of view, this behaviour involves underestimating the base-stock level, S, when a target fill rate is set for its determination. The method proposed in this paper overcomes these shortcomings.

The clean energy claims of BP, Chevron, ExxonMobil and Shell: A mismatch between discourse, actions and investments.

The energy products of oil and gas majors have contributed significantly to global greenhouse gas emissions (GHG) and planetary warming over the past century. Decarbonizing the global economy by mid-century to avoid dangerous climate change thus cannot occur without a profound transformation of their fossil fuel-based business models. Recently, several majors are increasingly discussing clean energy and climate change, pledging decarbonization strategies, and investing in alternative energies. Some even claim to be transforming into clean energy companies. Given a history of obstructive climate actions and "greenwashing", there is a need to objectively evaluate current and historical decarbonization efforts and investment behavior. This study focuses on two American (Chevron, ExxonMobil) and two European majors (BP, Shell). Using data collected over 2009-2020, we comparatively examine the extent of decarbonization and clean energy transition activity from three perspectives: (1) keyword use in annual reports (discourse); (2) business strategies (pledges and actions); and (3) production, expenditures and earnings for fossil fuels along with investments in clean energy (investments). We found a strong increase in discourse related to "climate", "low-carbon" and "transition", especially by BP and Shell. Similarly, we observed increasing tendencies toward strategies related to decarbonization and clean energy. But these are dominated by pledges rather than concrete actions. Moreover, the financial analysis reveals a continuing business model dependence on fossil fuels along with insignificant and opaque spending on clean energy. We thus conclude that the transition to clean energy business models is not occurring, since the magnitude of investments and actions does not match discourse. Until actions and investment behavior are brought into alignment with discourse, accusations of greenwashing appear well-founded.

Impact of organizational culture, occupational commitment and industry-academy cooperation on vocational education in China: Cross-sectional Hierarchical Linear Modeling analysis.

At a time when vocational education is seen as critical for national development, concern grows regarding how weak organizational culture and occupational commitment may threaten the production of quality graduates and teachers within the field. The failure of vocational institutions to effectively create human capital likely threatens the connections between Chinese industry and its educational institutions. This study thus explores how these connections are influenced by organizational and occupational factors. A multi-layer linear model is employed on data collected from 406 teachers from 69 Chinese vocational colleges and universities. Results suggest that organizational cultural positively influences industry-university cooperative behavior through the construction of strong occupational commitment and job involvement. This study not only enriches and expands new knowledge and academic perspectives, but also provides feasible policy suggestions to help guide educational administrators toward the improvement of vocational education.

Measurement and spatiotemporal analysis of high-quality development of China's industry.

BACKGROUND: China's economy has been transitioning from a phase of rapid growth to high-quality development. The high-quality development of industry is the foundation of a sustainable and healthy growth of national economy, and is of great significance to improve people's living standards, and to meet people's needs for a better life. METHODS: We develop an evaluation index system of high-quality development of industry from the perspectives of industrial benefit, innovation ability, coordination ability, green ability, opening ability and sharing ability. Based on a panel data of 30 provinces in China during 1999-2018, we evaluate the level of high-quality development of industry using the entropy-weight method and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. Meanwhile we select six specific years and adopt the Natural Breaks method to classify the provinces according to their levels. At last, Moran's I index is used to analyze the spatial correlation among the provinces. RESULTS: Opening ability and innovation ability are found to have greater impacts on industrial high-quality development than other indices, and their influence has been increasing in recent years. There are large spatial and temporal differences among different provinces. Municipalities and coastal provinces are found to be at constantly high levels. The levels in the central region dropped first and then increased, however it was the opposite in the western region. In the northeast region, the levels fluctuated greatly. Overall, the high-quality development of industry among China's provinces shows positive spatial correlation. Most provinces in China are in High-High and Low-Low clustering States. The High-High clustering type is mainly distributed in the eastern region and the Low-Low clustering type is mainly distributed in the western and central regions. CONCLUSION: (1) Innovation ability and open ability are the most important factors. (2) Green ability has not sufficiently contributed to China's industrial development. (3) Regional and time evolution differences are significant. (4) There is a significant and stable spatial clustering effect in the high-quality development of industry among China's provinces.

Research on the spatial association network structure for innovation efficiency of China's new energy vehicle industry and its influencing factors.

It is of great significance to study the spatial network of the new energy vehicle (NEV) industry innovation efficiency and its factors to promote the rational allocation of innovative resources and the coordinated development of Chinese NEV industry. First, the Super Efficiency Data Envelope Analysis model is used to measure innovation efficiency in the NEV industry in Chinese provinces, and based on the results, the improved gravity model is applied to construct a spatial correlation network. Then, by applying social network analysis (SNA) to study NEV industry development node spatial correlations, we conclude that there is no overall hierarchical structure. The SNA are applied to examine spatial correlations with respect to NEV industry innovation efficiency in each province, and to analyze the role and position of each province in the spatial correlation network. Finally, the influencing factors of spatial correlation of the innovation efficiency of China's NEV industry has been discussed. The result shows that the difference in spatial distance and R&D investment has a significant impact on the spatial correlation of the NEV industry.

Recommending blue ocean technologies for subcontractors: A framework based on business reports of prime contractors and patents.

Subcontractors depend heavily on their prime contractor and thus find it very risky to enter a new business on their own. This study proposes a framework for these subcontractors to develop blue ocean technologies related to their prime contractor. First, the primary technologies predicted to be promising are extracted from the business reports of the prime contractor. Sub-technologies are then selected through a patent-based search using keywords and International Patent Classification codes of the primary technologies. From them, blue ocean technologies are proposed by optimizing the weighted mean of the min-max normalized market value, degree of competition in the technology market, and subcontractors' potential technological capabilities for each sub-technology. This study shows that subcontractors can enhance their technology competitiveness by finding a low-risk blue ocean technology. Our empirical research on the subcontractors of a semiconductor firm identified technological patent fields for them to pursue. From our framework, subcontractors can identify blue ocean technologies by considering their prime contractor's future industrial areas and technologies of interest as well as their own technological capabilities. Furthermore, the prime contractors can gain the synergy effect of technology expansion through cooperation.

Environmental impacts, water footprint and cumulative energy demand of match industry in Pakistan.

A comprehensive life cycle assessment (LCA) was conducted for the matchsticks industry in the Khyber Pakhtunkhwa province of Pakistan to quantify environmental footprint, water footprint, cumulative energy use, and to identify improvement opportunities in the matchsticks manufacturing process. One carton of matchsticks was used as reference unit for this study. Foreground data was collected from the matchsticks industry through questionnaire surveys, personal meetings, and field measurements. The collected data was transformed into potential environmental impacts through the Centre for Environment Studies (CML) 2000 v.2.05 method present by default in the SimaPro v.9.1 software. Water footprint was calculated using methodology developed by Hoekstra et al., 2012 (water scarcity index) V1.02 and cumulative energy demand by SimaPro v.9.1 software. The results showed that transport of primary material (wood logs), sawn wood for matchsticks, red phosphorous, acrylic varnish, and kerosene fuel oil contributed to the overall environmental impacts. Transport of primary materials and sawn timber for matchsticks contributed significantly to abiotic depletion, global warming, eutrophication potential, ozone depletion, corrosion, human toxicity, and aquatic ecotoxicity effects. The total water footprint for manufacturing one carton of matchsticks was 0.265332 m3, whereas the total cumulative energy demand was 715.860 Mega Joules (MJ), mainly sourced from non-renewable fossil fuels (708.979 MJ). Scenario analysis was also conducted for 20% and 30% reduction in the primary material distance covered by trucks and revealed that reducing direct material transport distances could diminish environmental impacts and energy consumption. Therefore, environmental footprint could be minimized through diverting matchsticks industries freight from indigenous routes to high mobility highways and by promoting industrial forestry close to industrial zones in Pakistan. Many industries did not have emissions control systems, exceeding the permissible limit for emissions established by the National Environmental Quality Standards (NEQS) of Pakistan. Thus, installation of emissions control system could also diminish emissions from match industry in Pakistan.

Which ship-integrated power system enterprises are more competitive from the perspective of patent?

By analyzing the relevant patent data, the technological competitiveness of enterprises can be objectively evaluated, and the research and development priorities and the technological advantages and disadvantages of each enterprise in the same field can be compared and analyzed. It is considered to be helpful in judging the patent strategy, innovation ability, and the innovation level of enterprises, which is of great practical significance. Based on the field of the ship-integrated power system as an example, considering the Derwent patent holder code, draw the integrated technical strength of ships in the field of the distribution power system; using the ideas of the Boston matrix to measure the field has the competitive advantage of enterprises; by using the social network analysis method for each enterprise, the core technology of mining, based on the S curve of the technology life cycle, analyzes the enterprise concentration each time in order to predict the future trend of development. It can be found that China Shipbuilding Industry Corporation has the largest number of patents, followed by Fuji Electric Co. Ltd, International General Electric, Daewoo shipbuilding ocean engineering Co. Ltd and so on. Considering the patent quantity and the patent quality, the dominant and productive enterprises in this field can be distinguished. The ship-integrated power system and its related core technologies have been rapidly growing at present. The related technology patents will increase rapidly in the next few years, and more and more enterprises will participate in this field.

Positive effects of COVID-19 lockdown on air quality of industrial cities (Ankleshwar and Vapi) of Western India.

On January 30, 2020, India recorded its first COVID-19 positive case in Kerala, which was followed by a nationwide lockdown extended in four different phases from 25th March to 31st May, 2020, and an unlock period thereafter. The lockdown has led to colossal economic loss to India; however, it has come as a respite to the environment. Utilizing the air quality index (AQI) data recorded during this adverse time, the present study is undertaken to assess the impact of lockdown on the air quality of Ankleshwar and Vapi, Gujarat, India. The AQI data obtained from the Central Pollution Control Board was assessed for four lockdown phases. We compared air quality data for the unlock phase with a coinciding period in 2019 to determine the changes in pollutant concentrations during the lockdown, analyzing daily AQI data for six pollutants (PM10, PM2.5, CO, NO2, O3, and SO2). A meta-analysis of continuous data was performed to determine the mean and standard deviation of each lockdown phase, and their differences were computed in percentage in comparison to 2019; along with the linear correlation analysis and linear regression analysis to determine the relationship among the air pollutants and their trend for the lockdown days. The results revealed different patterns of gradual to a rapid reduction in most of the pollutant concentrations (PM10, PM2.5, CO, SO2), and an increment in ozone concentration was observed due to a drastic reduction in NO2 by 80.18%. Later, increases in other pollutants were also observed as the restrictions were eased during phase-4 and unlock 1. The comparison between the two cities found that factors like distance from the Arabian coast and different industrial setups played a vital role in different emission trends.

Industry Actor Use of Research Evidence: Critical Analysis of Australian Alcohol Policy Submissions.

OBJECTIVE: Governments' limited adoption of evidence-based policies to reduce alcohol-related harm has been partly attributed to alcohol industry influence. A better understanding of industry political strategy may help protect public policy against vested interests. We examined how industry actors used scientific evidence in their submissions to government alcohol policy consultations. METHOD: We conducted a content analysis of 214 submissions from industry actors in 21 Australian public consultations between 2013 and 2017. Represented industry actors included alcohol producers and retailers, trade associations, licensees, and associated entities that derive commercial benefit from alcohol (e.g., advertising companies). Adapting an existing framework, we classified industry practices into two categories: (a) misuse of evidence and (b) denial of the effectiveness of evidence-based strategies. RESULTS: Almost all submissions (91%) denied the effectiveness of evidence-based strategies; the most common denial practices were making unsubstantiated claims about adverse effects of policies (76%) and promoting alternatives without evidence (71%). The misuse of scientific evidence was apparent in 66% of submissions. Trade associations, producers, and retailers were most likely to use such practices. CONCLUSIONS: The extent to which the examined industry actors misused scientific evidence in their submissions to a wide range of alcohol policy consultations in Australia suggests the need for governments to consider excluding the industry from consultation on the regulation of alcohol.

COVID-19: Lessons from a construction site, can we apply one industry safety protocol to another?

More than six months after the Shelter-in-Place executive order in the San Francisco Bay Area, this paper analyzes how an essential public works construction project put a COVID-19 safety protocol in place. It describes a four-step protocol, details challenges and successes of implementation, and provides insight for construction as well as other industries, including healthcare.

Public Health versus Alcohol Industry Compliance Laws: A Case of Industry Capture?

This article confirms that industry compliance and enforcement processes are an essential consideration in the growing pantheon of legal and commercial determinants of public health. While alcohol control laws vary between individual jurisdictions, their development and application are confronted by a common threat of undue industry influence or capture. This necessitates a greater understanding of this phenomenon to better inform a collective and effective international public health response. New South Wales Australia, has developed a layer of alcohol industry compliance laws in the form of disciplinary schemes. This article critically explicates the first of these, the Violent Venues Scheme (VVS), to determine the nature and extent of any capture. This would significantly compromise harm minimisation statutory objects and disrupt the democratic process and the rule of law. In contrast, an influential industry identity, attributed the earlier last drinks laws, VVS and a related scheme as causing the alleged destruction of Sydney's nighttime economy and fun. The research also analyses the indispensible role of a neoliberal paradigm in legitimising exclusive relationships between governments and industry. This is indelibly imprinted on the alcohol regulatory landscape.

Strategies in genotoxicology: Acceptance of innovative scientific methods in a regulatory context and from an industrial perspective.

The tests used and the general principles behind test strategies are now often over 30 years old. It may be time by now, given that our knowledge of genetic toxicology has improved and that we also technically are better able to investigate DNA damage making use of modern molecular biological techniques, to start thinking on a new test strategy. In the present paper, it is discussed that the time is there to consider a new approach for genotoxicity assessment of substances. A fit for all test strategy was discussed making use of the most recent technological methods and techniques. It was also indicated that in silico tools should be more accepted by regulatory institutes/bodies as supporting information to better conclude which tests should be required for each separate substance to demonstrate its genotoxic potency. Next to that there should be a good rationale for performing in vivo studies. Finally, the need for germ cell genotoxicity testing, essential when classification and labeling of substances is mandatory, was discussed. It was suggested to change the GHS for genotoxicity classification and labelling from in vivo tests in germ cells into in vivo tests in somatic cells. Quantitative genotoxicology was also discussed. It appeared that we are currently at a transition, where the science developing to justify carrying out human health risk assessments based on genetic toxicology data sets supported by mechanistic data and exposure data. However, implementation will take time, and acceptance will be supported through the development of numerous case studies. Major remaining questions are: is genetic damage a relevant endpoint in itself, or should the risk assessment be carried out on the apical endpoint of cancer and which genotoxic endpoint should be used to derive the point of departure (PoD) for the human exposure limit?