Adjacent Positions Research Articles

Precise pulmonary scanning and reducing medical radiation exposure by developing a clinically applicable intelligent CT system: Toward improving patient care.

BackgroundInterstitial lung disease requires frequent re-examination, which directly causes excessive cumulative radiation exposure. To date, AI has not been applied to CT for enhancing clinical care; thus, we hypothesize AI may empower CT with intelligence to realize automatic and accurate pulmonary scanning, thus dramatically decrease medical radiation exposure without compromising patient care.MethodsFacial boundary detection was realized by recognizing adjacent jaw position through training and testing a region proposal network (RPN) on 76,882 human faces using a preinstalled 2-dimensional camera; the lung-fields was then segmented by V-Net on another training set with 314 subjects and calculated the moving distance of the scanning couch based on a pre-generated calibration table. A multi-cohort study, including 1,186 patients was used for validation and radiation dose quantification under three clinical scenarios.FindingsA U-HAPPY (United imaging Human Automatic Planbox for PulmonarY) scanning CT was designed. Error distance of RPN was 4·46±0·02 pixels with a success rate of 98·7% in training set and 2·23±0·10 pixels with 100% success rate in testing set. Average Dice's coefficient was 0·99 in training set and 0·96 in testing set. A calibration table with 1,344,000 matches was generated to support the linkage between camera and scanner. This real-time automation makes an accurate plan-box to cover exact location and area needed to scan, thus reducing amounts of radiation exposures significantly (all, P<0·001).InterpretationU-HAPPY CT designed for pulmonary imaging acquisition standardization is promising for reducing patient risk and optimizing public health expenditures.FundingThe National Natural Science Foundation of China.

Differentiation and functionalization of remote C-H bonds in adjacent positions.

Site-selective functionalization of C–H bonds will ultimately afford chemists transformative tools for editing and constructing complex molecular architectures. Towards this goal, developing strategies to activate C–H bonds that are distal from a functional group is essential. In this context, distinguishing remote C–H bonds on adjacent carbon atoms is an extraordinary challenge due to the lack of electronic or steric bias between the two positions. Herein, we report the design of a catalytic system leveraging a remote directing template and a transient norbornene mediator to selectively activate a previously inaccessible remote C–H bond that is one bond further away. The generality of this approach has been demonstrated with a range of heterocycles, including a complex anti-leukemia agent, and hydrocinnamic acid substrates.

Stereoselective Bioreduction of α-diazo-β-keto Esters.

Diazo compounds are versatile reagents in chemical synthesis and biology due to the tunable reactivity of the diazo functionality and its compatibility with living systems. Much effort has been made in recent years to explore their accessibility and synthetic potential; however, their preparation through stereoselective enzymatic asymmetric synthesis has been scarcely reported in the literature. Alcohol dehydrogenases (ADHs, also called ketoreductases, KREDs) are powerful redox enzymes able to reduce carbonyl compounds in a highly stereoselective manner. Herein, we have developed the synthesis and subsequent bioreduction of nine α-diazo-β-keto esters to give optically active α-diazo-β-hydroxy esters with potential applications as chiral building blocks in chemical synthesis. Therefore, the syntheses of prochiral α-diazo-β-keto esters bearing different substitution patterns at the adjacent position of the ketone group (N3CH2, ClCH2, BrCH2, CH3OCH2, NCSCH2, CH3, and Ph) and in the alkoxy portion of the ester functionality (Me, Et, and Bn), were carried out through the diazo transfer reaction to the corresponding β-keto esters in good to excellent yields (81–96%). After performing the chemical reduction of α-diazo-β-keto esters with sodium borohydride and developing robust analytical conditions to monitor the biotransformations, their bioreductions were exhaustively studied using in-house made Escherichia coli overexpressed and commercially available KREDs. Remarkably, the corresponding α-diazo-β-hydroxy esters were obtained in moderate to excellent conversions (60 to >99%) and high selectivities (85 to >99% ee) after 24 h at 30 °C. The best biotransformations in terms of conversion and enantiomeric excess were successfully scaled up to give the expected chiral alcohols with almost the same activity and selectivity values observed in the enzyme screening experiments.

Theory and performance analyses in quantum stream cipher based on bitwise NOT operation

Because of the realization of physical layer security, the Quantum Stream Cipher (QSC) is getting more and more attention. However, the error rate of each bit of ciphertexts is different from 0.5 for Eve in QSC. This drawback provides Eve with an opportunity to break QSC system possibly through some attacks, such as fast correlation attacks. Thus, to increase the bit error rate of ciphertexts in the higher bit positions to cope with this kind of attacks, this paper proposes a ciphertext mapping method based on Bitwise NOT Operation (BNO). According to parity of bases, BNO-based mapping performs bitwise NOT operation for some bit positions of ciphertext to expand the difference between adjacent bit positions of ciphertexts in QSC. Besides, BNO-based QSC can be directly employed in multi-bit plaintext mapping in QSC for different modulation formats, such as PSK/QSC and QAM/QSC. The security and transmission performance of QSC based on BNO are mainly investigated with different intensity ASE noises and the number of bases in optical back-to-back simulation. The simulation results demonstrate that bit error rate in each bit position of ciphertext is close to 0.5 by BNO method in QSC. Thus, BNO method can expand the impact of noise on the higher bit positions of ciphertext. In addition, BNO method has little influence on transmission performance of receiver in QSC system.

Latin Case System: Towards a Motivated Paradigmatic Structure

The article attempts, firstly, to critically analyze the traditional order of cases in Latin, secondly, to discover an internal mechanism that brings the elements of a paradigm together, and thirdly, to present a new model of the nominal and pronominal case paradigms in Latin. The authors develop the idea that the crucial role in structuring a case paradigm belongs to morphemic syncretism. The syncretism is treated as a systemic phenomenon of morpheme neutralization rather than a result of phonetic reduction. In the paradigm built on this principle, the cases marked with the same endings necessarily take adjacent positions. There is a certain correlation between the morphemic syncretism and the semantics of cases extensively exemplified in the Latin literature. Taking this as reference point, the authors establish a formally motivated paradigmatic order of cases and single out a set of semantic features that shape the case paradigm. This method enables authors to find the non-contradictory paradigmatic positions for both the core and the “marginal” cases (vocative and locative). Applied to the pronominal cases, however, it reveals the significant discrepancy between the nominal and pronominal paradigms concerning two cases — nominative and genitive. The pronominal nominative’s special status is determined by its pragmatic rather than syntactic functions, which is typical for pro-drop languages. The genitive case appears in three different forms that originate from the possessive pronouns and correspond to the three basic functions of the genitive — possessive, objective, and partitive ones. Such transparadigmatic syncretism brings together the paradigms of personal and possessive pronouns, which are related by nature. The approach suggested in this study makes it possible to present in a new way the nominal and pronominal case paradigms, to demonstrate in what points they differ from each other, and to highlight some functional and semantic features of the particular cases.

Optimization of optical control of nitrogen vacancy centers in solid diamond

The nitrogen-vacancy (NV) centers in diamond have the advantages of stable triaxial structure, ultra-long electron spin coherence time and simple optical readout at room temperature. A nitrogen atom in the diamond crystal replaces a carbon atom and a vacancy is generated at the adjacent position, forming a point defect in the &lt;i&gt;C&lt;/i&gt;&lt;sub&gt;3&lt;i&gt;v&lt;/i&gt;&lt;/sub&gt; space group structure. Its ground state and excited state are both spin triplet states. It is the key to achieving efficient preparation of optical initial state and extracting NV color center’s information in the researches of highly sensitive sensing magnetic detection, temperature detection, biological imaging, quantum computing, etc. However, there was no systematic study on relevant parameters of laser for high-concentration NV color center’s samples in previous experimental studies. Based on a high concentration diamond NV ensemble, we use pulsed optical detection magnetic resonance (ODMR) technology to systematically study the relationship among laser initial polarization time, information reading time and laser power, and the influence of laser incident polarization angle on the accuracy of sensing information. The effects of various laser parameters on the NV1 peak of ODMR on the [111] axis of the NVs of diamond are also investigated. The contrast of ODMR increases firstly with a sigmoid function and then decreases with an e-exponential function as the information reading time increases. The incident polarization angle of the laser is sinusoidal, with a period of 90°. According to the above experimental results, we finally choose the appropriate experimental parameters at 45.8 W/cm&lt;sup&gt;2&lt;/sup&gt; (300 μs of polarization, 700 ns, reading time, laser incident angle is 220°) for ODMR test. Compared with previous experimental parameters (polarization time was 50 us, read the time of 3000 ns, laser incident angle was 250°), the experimental results show that the contrast of ODMR increases from 2.1% to 4.6%, and the typical magnetic sensitivity is improved from 21.6 nT/Hz&lt;sup&gt;1/2&lt;/sup&gt; to 5.6 nT/Hz&lt;sup&gt;1/2&lt;/sup&gt;. The optimization of the optical control of NVs in solid diamond is realized. The above results provide an effective support for the detection of high-sensitivity manipulation sensing based on high-concentration NV ensemble.

Social-Aware D2D Video Delivery Method Based on Mobility Similarity Measurement in 5G Ultra-Dense Network

The huge amounts of network traffic generated by the ultra-high-definition video playback of super-large-scale video users results in tremendous pressure for front-haul and back-haul in the 5G network, which brings severely negative influence for the large-scale deployment and scalability of video systems and video delivery performance (e.g. transmission delay and packet loss) related to user quality of experience. The direct D2D communications between mobile devices with adjacent position in geographical area can offloading huge video traffic into the underlying networks, which reduces load of cellular base station in the edge networks and relieves traffic pressure in the core networks. In this paper, we propose a novel Social-Aware D2D Video Delivery Method based on Rapid Sample-Efficient Measurement of Mobility Similarity in 5G Ultra-Dense Network (DMSEM). By investigation for one-hop D2D pair relationship, DMSEM builds a social state transition model of user movement, which makes use of encounter duration and shared video length between encountered users to define the state transition condition. A cluster algorithm of encounter events is proposed, which achieves initial clusters of encounter events by calculating similarity between encounter events from the two aspects of both variation rate of geographical distance between mobile users and encounter duration time. DMSEM makes use of the Fuzzy C-Means to refine the initial clusters and extracts encounter patterns of mobile users. DMSEM designs a sample-efficiency rapid recognition algorithm of encounter pattern, which can use small number of encounter distance samples to achieve fast heuristic recognition of encounter pattern. Extensive tests show how DMSEM achieves better results in comparison with other state-of-the-art solutions in terms of packet loss rate, average freeze time, cache utilization, average bitrate, buffer level and control overhead.

Precise Pulmonary Scanning and Reducing Medical Radiation Exposure by Developing a Clinically Applicable Intelligent CT System: Towards Improving Patient Care

Background: Interstitial lung disease requires frequent re-examination, which directly causes excessive cumulative radiation exposure. To date, AI has not been applied to CT for enhancing clinical care; thus, we hypothesize AI may empower CT with intelligence to realize automatic and accurate pulmonary scanning, thus dramatically decrease medical radiation exposure without compromising patient care. Methods: Facial boundary detection was realized by recognizing adjacent jaw position through training and testing a region proposal network (RPN) on 76,882 human faces using a preinstalled 2-dimensional camera; the lung-fields was then segmented by V-Net on another training set with 314 subjects and calculated the moving distance of the scanning couch based on a pre-generated calibration table. A multi-cohort study, including 1,186 patients was used for validation and radiation dose quantification under three clinical scenarios. Findings: A U-HAPPY (United imaging Human Automatic Planbox for PulmonarY) scanning CT was designed. Error distance of RPN was 4·46±0·02mm with a success rate of 98·7% in training set and 2·23±0·10mm with 100% success rate in testing set. Average Dice’s coefficient was 0·99 in training set and 0·96 in testing set. A calibration table with 1,344,000 matches was generated to support the linkage between camera and scanner. This real-time automation makes an accurate plan-box to cover exact location and area needed to scan, thus reducing amounts of radiation exposures significantly (all, P <0·001). Interpretation: U-HAPPY CT designed for pulmonary imaging acquisition standardization is promising for reducing patient risk and optimizing public health expenditures. Funding Statement: This work was supported by the National Natural Science Foundation of China (81720108022, 91649116, 81571040, 81973145), the Social Development Project of Science and Technology in Jiangsu Province (BE2016605, BE201707), the National Key R&D Program of China (2017YFC0112801), the Key Medical Talents of Jiangsu Province, the ‘13th Five-Year’ Health Promotion Project of Jiangsu Province (B.Z.2016-2020), the Jiangsu Provincial Key Medical Discipline (Laboratory) (ZDXKA2016020), the Project of the Sixth Peak of Talented People (WSN-138, BZ), the China Postdoctoral Science Foundation (2019M651805), the Fundamental Research Funds for the Central Universities grants of China (Grant No. 2632018FY04), the “Double First-Class” University project (CPU2018GY09). Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: This study was approved by the institutional review board of The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School. Institutional review board (IRB)/ethics committee approvals were obtained. This work was conducted in a manner compliant with the People's Republic of China Health Insurance Portability and Accountability Act and was adherent to the tenets of the Declaration of Helsinki. Patient consents were waived by IRB.

Interactive Rule Attention Network for Aspect-Level Sentiment Analysis

Aspect-level sentiment analysis is a fundamental task in NLP, and it aims to predict the sentiment polarity of each specific aspect term in a given sentence. Recent researches show that the fine-grained sentiment analysis for aspect-level has become a research hotspot. However, previous work did not consider the influence of grammatical rules on aspect-level sentiment analysis. In addition, attention mechanism is too simple to learn attention information from context and target interactively. Therefore, we propose an interactive rule attention network (IRAN) for aspect-level sentiment analysis. IRAN not only designs a grammar rule encoder, which simulates the grammatical functions at the sentence by standardizing the output of adjacent positions, but also constructs an interaction attention network to learn attention information from context and target. Experimental results on SemEval 2014 Dataset and ACL 2014 Twitter Dataset demonstrate IRAN can learn effective features and obtain superior performance over the baseline models.

Detection and Prevention of Manet using Hybrid SVM with Ann

Mobile Ad hoc Networks (MANET) have been exceptionally vulnerable against attacks because of the dynamic and self-configurable nature of its system foundation. This kind of wireless network is appropriate for temporary communication linked due to its nature of less-foundation and there is no any control of centralized manner. Design a routing mechanism that are security aware with higher QoS parameter is very competetive and the major tasks involved in ad hoc types of network as per the limited power resources and their dynamic routing topology. This paper mainly focused on the design of a secure and trusts based on-demand routing mechanism using Ad-hoc on demand distance vector (AODV) protocol to compute trust-based produces path initialed from source up to destination that will fulfill minimum two end-to-end QoS parameters of network. So here, the generalized AODV routing protocol has been extended from traditional routing mechanism to analyze the performance of this model with combination of artificial intelligence concept. The proposed ad hoc based routing mechanism is used to found possible routes that are prevented through trust adjacent position of security validation protocols and enhanced link optimized route computes on the basis of Artificial Neural Network (ANN) as an artificial intelligence algorithm for well-organized communication in MANET. In addition, this research demonstrates the effectiveness of bio inspired Firefly Algorithm (FFA) as an optimization approach with the consideration of several performance QoS metrics of network. The results have been measured in terms of throughput and PDR with SVM and ANN approach. It has been observed that the throughput and PDR measured using ANN approach is better compared to SVM approach an average of 0.755 PDR value has been obtained using ANN approach.

Interleaved 31 P MRS/1 H ASL for analysis of metabolic and functional heterogeneity along human lower leg muscles at 7T.

PurposeMR offers the unique possibility to noninvasively investigate cellular energy metabolism via 31P MRS, while blood perfusion, which provides oxygen and substrates to the tissue, is accessible by arterial spin labeling (ASL) 1H MRI. Because metabolic and hemodynamic parameters are linked, it would be desirable to study them simultaneously. A 3D‐resolved method is presented that allows such measurements with high spatiotemporal resolution and has the potential to discern differences along an exercising muscle.MethodsMulti‐voxel localized 31P MRS was temporally interleaved with multi‐slice pASL 1H MRI. Phosphorus spectra were collected from two adjacent positions in gastrocnemius medialis (GM) during rest, submaximal plantar flexion exercise and recovery, while perfusion and T2*‐weighted axial images were acquired at the same time. Seventeen healthy volunteers (9 f / 8 m) were studied at 7 T.ResultsAn increase of postexercise perfusion and T2*‐weighted signal in GM positively correlated with end‐exercise PCr depletion and pH drop. At proximal positions functional and metabolic activity was higher than distally, that is, perfusion increase and peak T2*‐weighted signal, end‐exercise PCr depletion, end‐exercise pH, and PCr recovery time constant were significantly different. An NOE‐induced SNR increase of approximately 20 % (P < .001), at rest, was found in interleaved 31P spectra, when comparing to 31P‐only acquisitions.ConclusionsA technique for fast, simultaneous imaging of muscle functional heterogeneity in ASL, T2* and acquisition of time‐resolved 31P MRS data is presented. These single exercise recovery experiments can be used to investigate local variations during disease progression in patients suffering from vascular or muscular diseases.

Influence of collars on reduction in scour depth at two piers in a tandem configuration

Bridge failure, due to local scour at bridge pier foundations, has become a critical issue in river and bridge engineering, which might lead to transportation disruption, loss of lives and economic problems. A practical solution to prevent bridge collapses is the implementation of scour mitigation methods around bridge foundations. Based on an experimental perspective, this study is focused on the influence of the size and position of circular collars from the sediment bed on scour depth at two tandem piers. To meet this end, long-lasting experiments are performed under clear-water conditions using uniform sand for bed materials. Compared to the adjacent position of the collar on the bed, placing the collars below the bed would increase the delay time of scour at the piers up to four times. However, regardless of the delay time, the observations indicate that locating the collars on the initial bed surface results in maximum reduction in scour depths around the piers. It was found that diminishing the flow intensity has a dramatic impact on the scour reduction at the piers, so that maximum reduction in scour depths at piers increased on average from 20 to 70% with the reduction in the flow intensity from 0.95 to 0.9.

Sugar Puckering Drives G-Quadruplex Refolding: Implications for V-Shaped Loops.

A DNA G‐quadruplex adopting a (3+1) hybrid structure was modified in two adjacent syn positions of the antiparallel strand with anti‐favoring 2′‐deoxy‐2′‐fluoro‐riboguanosine (FrG) analogues. The two substitutions promoted a structural rearrangement to a topology with the 5′‐terminal G residue located in the central tetrad and the two modified residues linked by a V‐shaped zero‐nucleotide loop. Strikingly, whereas a sugar pucker in the preferred north domain is found for both modified nucleotides, the FrG analogue preceding the V‐loop is forced to adopt the unfavored syn conformation in the new quadruplex fold. Apparently, a preferred C3′‐endo sugar pucker within the V‐loop architecture outweighs the propensity of the FrG analogue to adopt an anti glycosidic conformation. Refolding into a V‐loop topology is likewise observed for a sequence modified at corresponding positions with two riboguanosine substitutions. In contrast, 2′‐F‐arabinoguanosine analogues with their favored south‐east sugar conformation do not support formation of the V‐loop topology. Examination of known G‐quadruplexes with a V‐shaped loop highlights the critical role of the sugar conformation for this distinct structural motif.

Encoder–decoder with double spatial pyramid for semantic segmentation

Semantic segmentation, as a dense pixelwise classification task, is of great significance to scene understanding. Many approaches based on convolutional neural network still suffer from two kinds of challenges: (1) insufficient semantic information results in semantic obfuscation between similar categories, (2) loss of spatial information leads to inaccurate location of inconspicuous objects. To tackle these challenges, we design a network with an encoder–decoder architecture based on two proposed modules: global pyramid attention module (GPAM) and pyramid decoder module (PDM). Specifically, GPAM exploits an attention mechanism as global prior knowledge to adaptively capture discriminative features for enhancing semantic representation, and PDM employs small convolutions connected in parallel to predict adjacent position relationships for refining spatial information. A series of ablation experiments are conducted to demonstrate the effectiveness of our designs, and our network achieves a mean intersection over union score of 83.4% on PASCAL VOC 2012 dataset and 78.5% on Cityscapes dataset.

Propeller-like acceptors with difluoride perylene diimides for organic solar cells

Abstract Perylene diimide (PDI) is one of most intensively studied non-fullerene small molecule acceptors (SMAs). By fluorination on the conjugated backbone, a new PDI with difluoride substitution on adjacent bay positions of PDI is prepared. Then, four propeller-like SMAs are obtained by linking four PDIs with an aromatic core, wherein the molecular geometry is modulated by ring fusion of the aromatic core. Further study reveals that fluorination is helpful to enhance the absorption intensity, and thus promote the current density in organic solar cells. In addition, the ring-fused strategy is able to suppress the distortion and rotation of relevant molecules. Therefore, these four acceptors exhibit significantly diversity of photovoltaic performance, wherein the acceptor FPDIF4-DTC consisting of a fused core and fluoro-substituted PDIs shows a best efficiency of 5.1%. This result implies that fluorination on PDI conjugated backbone is a successful way to construct promising SMAs.

Genome-Wide Variant Identification and High-Density Genetic Map Construction Using RADseq for Platycladus orientalis (Cupressaceae).

Platycladus orientalis is an ecologically important native conifer in Northern China and exotic species in many parts of the world; however, knowledge about the species’ genetics and genome are very limited. The availability of well-developed battery of genetic markers, with large genome coverage, is a prerequisite for the species genetic dissection of adaptive attributes and efficient selective breeding. Here, we present a genome-wide genotyping method with double-digestion restriction site associated DNA sequencing (ddRAD-seq) that is effective in generating large number of Mendelian markers for genome mapping and other genetic applications. Using 139 megagametophytes collected from a single mother tree, we assembled 397,226 loci, of which 108,683 (27.4%) were polymorphic. After stringent filtering for 1:1 segregation ratio and missing rate of <20%, the remaining 23,926 loci (22% of the polymorphic loci) were ordered into 11 linkage groups (LGs) and distributed across 7,559 unique positions, with a total map length of 1,443 cM and an average spacing of 0.2 cM between adjacent unique positions. The 11 LGs correspond to the species’ 11 haploid genome chromosome number. This genetic map is among few high-density maps available for conifers to date, and represents the first genetic map for P. orientalis. The information generated serves as a solid foundation not only for marker-assisted breeding efforts, but also for comparative conifer genomic studies.

Application effects of enhanced computed tomography and three-dimensional reconstruction technology in reconstruction of pediatric post-burn scars with expanded flaps

Objective: To explore the application effects of enhanced computed tomography (CT) and three-dimensional reconstruction technology in the reconstruction of pediatric post-burn scars with expanded flaps. Methods: From May 2016 to March 2019, 19 children with hypertrophic scars after thermal injuries were admitted to our unit, including 10 boys and 9 girls, aged from 4 years and 5 months to 15 years and 11 months. The area of scars ranged from 5 cm×4 cm to 23 cm×9 cm. One or more skin and soft tissue expanders with suitable volume and shape were implanted into the normal skin area around scar of children. Three to six months later, enhanced CT and three-dimensional reconstruction were performed before the second stage operation to obtain three-dimensional images of the vascular branches in the donor site for expanded flaps to be cut, so as to determine the course and distribution of the vascular branches and guide the design of expanded flaps. According to the design scheme, the resection of scar, removal of expanders, and excision and transfer of flaps were performed to repair the wounds after scar resection. The area of flaps ranged from 6 cm×4 cm to 25 cm×10 cm. The donor site was closed directly. The number of flaps was counted. The anatomical structure, vascular distribution, and adverse reactions during enhanced CT and three-dimensional reconstruction of site for expanded flaps to be cut, the survival of expanded flaps and the follow-up after the second-stage operation were observed. Results: A total of 48 expanded flaps were designed and excised in 19 children. The anatomical structure of the site for expanded flaps to be cut and the adjacent spatial position relationship were visually observed through the three-dimensional reconstruction after enhanced CT, and no adverse reactions were observed. Arterial branch blood supply or venous return was observed in 29 sites for expanded flaps to be cut. All the expanded flaps survived well without blood supply disorder after the second stage operation. The children were followed up for 6 months to 1 year and 6 months after the second stage operation. The appearance of the flaps was natural, and the color and thickness of the flaps were similar to those of the surrounding normal skin, except for one child with obvious linear scar. Conclusions: Enhanced CT and three-dimensional reconstruction can assist the vascular assessment of the expended flaps, which is helpful for rational design of the flap excision and transfer protocol to improve the survival rate of flaps. Thus, it has certain clinical application value in the reconstruction of post-burn scar in children with expanded flaps.

INDOMARET MILIK SIAPA? IMPLEMENTASI DAN PEMINGGIRAN PEDAGANG KECIL DALAM PRAKTEK PEMBERIAN IZIN MENDIRIKAN TOKO MODERN DI MEULABOH

Implementation of the Republic of Indonesia's Minister of Trade Regulation regarding the presence of modern shops such as Indomaret in Meulaboh City, West Aceh Regency, which has an impact on the large number of Indomarets and disrupts the existence of traditional shops owned by local communities. This study used a qualitative method through a case study approach with key informants as Head of Trade at the Trade Office, Head of Services and Licensing Staff of the One-Stop Integrated Investment and Services Office (DPMPTSP), Secretary of the West Aceh Traders Association, Modern Shop Employees ( Indomaret), Traditional Traders / Grocer and Community Traders. The results of this study indicate that the implementation of the Permendagri issuance, especially related to structuring guidelines and fostering of traditional markets, shopping centers and modern shops carried out by the Regional Government of West Aceh Regency has not been fully effective, it is due to the absence of derivative policies governing further related the establishment of modern markets such as Indomaret, and in the implementation there is also communication and non-coordination between the two parties implementing the policy. Aside from having positive impacts such as increasing local revenue tax, Indomaret's presence also has a negative impact because it increasingly marginalizes and even kills merchant businesses in traditional shops due to shifts in consumer habits, distance or adjacent positions between modern and traditional stores.

Helix Breaking Transition in the S4 of HCN Channel is Critical for Hyperpolarization-Dependent Gating

HCN channels, unlike other members of the VGIC superfamily, open upon hyperpolarization rather than depolarization. Structural and functional analyses reveal that the voltage-sensor of these channels are unique but the mechanisms that lead to inward rectification remain poorly understood. Here, using all-atom molecular dynamics simulations under hyperpolarization conditions, we report that the S4 voltage-sensor of HCN channels initially moves downward but, upon transfer of the last gating charge, breaks into two sub-helices with the lower sub-helix becoming parallel to the membrane plane. Substitution of the serine at the breakpoint with a hydrophobic residue favors outward rectification but this effect can be reversed by inserting a serine in an adjacent position. We find that the gating polarity strongly correlates with hydrophilicity and helical turn propensity of the substituents at the breakpoint. Our studies reveal an unexpected mechanism of inward rectification involving a linker sub-helix emerging from HCN S4 during hyperpolarization.

Clinically Applicable Deep Learning to Automate Pulmonary Scanning: Towards Building Intelligent CT Systems

Background: Artificial intelligence (AI) has not been experimented with the enhancement of the upstream clinical care, especially imaging acquisition; thus, we hypothesize AI may empower CT with intelligence. We herein combine two state-of-the-art deep learning architectures for object detection and semantic segmentation to build an intelligent system to automate pulmonary scanning and reduce radiation dose. Methods: Facial boundary detection was realized by ingeniously recognizing the adjacent jaw position through training and testing a region proposal network (RPN) on 76,882 human faces after a preinstalled 2-dimensional camera; we then segmented the lung-fields by deploying V-Net on another training set with 314 subjects and calculated the moving distance of scanning couch based on a pre-generated calibration table. A multi-cohort comprising 1,186 patients was used for independent validation and radiation dose quantification under three clinical scenarios. Findings: A U-HAPPY (United imaging Human Automatic Planbox for PulmonarY) scanning CT was designed. The error distance of RPN was 4·46±0·02mm with a success rate of 98·7% in the training set and 2·23±0·10mm with 100% success rate in the testing set. The average Dice's coefficient was 0·99 in the training set and 0·96 in the testing set. A calibration table with 1,344,000 matches was generated to support the linkage between the camera and scanner. This real-time automation makes an accurate planbox to cover exact location and area that needs to scan, which thus reduces amounts of radiation exposures significantly in scenario fully navigated by U-HAPPY as compared to others (all, P<0·001). Interpretation: Our U-HAPPY CT designed for pulmonary imaging acquisition standardization and upstream workflow optimization may complete the last puzzle piece that combines AI and medical imaging. Funding Statement: This work was supported by the National Natural Science Foundation of China (81720108022, 91649116, 81571040, 81973145), the Social Development Project of Science and Technology in Jiangsu Province (BE2016605, BE201707), the National Key R&D Program of China (2017YFC0112801), the Key Medical Talents of Jiangsu Province, the ‘13th Five-Year’ Health Promotion Project of Jiangsu Province (B.Z.2016-2020), the Jiangsu Provincial Key Medical Discipline (Laboratory) (ZDXKA2016020), the Project of the Sixth Peak of Talented People (WSN-138, BZ), the China Postdoctoral Science Foundation (2019M651805), the Fundamental Research Funds for the Central Universities grants of China (Grant No. 2632018FY04), the “Double First-Class” University project (CPU2018GY09). Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: The study was approved by the institutional review board of the Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School. Institutional review board (IRB)/ethics committee approvals were obtained. The work was conducted in a manner compliant with the People's Republic of China Health Insurance Portability and Accountability Act (HIPAA) and was adherent to the tenets of the Declaration of Helsinki. Patient consent was waived for access to the training, validation, and independent testing datasets.